Combination of DNA-based and conventional methods to detect human leukocyte antigen polymorphism and its use for paternity testing.

PubMed

Kereszturya, László; Rajczya, Katalin; Lászikb, András; Gyódia, Eva; Pénzes, Mária; Falus, András; Petrányia, Gyõzõ G

2002-03-01

In cases of disputed paternity, the scientific goal is to promote either the exclusion of a falsely accused man or the affiliation of the alleged father. Until now, in addition to anthropologic characteristics, the determination of genetic markers included human leukocyte antigen gene variants; erythrocyte antigens and serum proteins were used for that reason. Recombinant DNA techniques provided a new set of highly variable genetic markers based on DNA nucleotide sequence polymorphism. From the practical standpoint, the application of these techniques to paternity testing provides greater versatility than do conventional genetic marker systems. The use of methods to detect the polymorphism of human leukocyte antigen loci significantly increases the chance of validation of ambiguous results in paternity testing. The outcome of 2384 paternity cases investigated by serologic and/or DNA-based human leukocyte antigen typing was statistically analyzed. Different cases solved by DNA typing are presented involving cases with one or two accused men, exclusions and nonexclusions, and tests of the paternity of a deceased man. The results provide evidence for the advantage of the combined application of various techniques in forensic diagnostics and emphasizes the outstanding possibilities of DNA-based assays. Representative examples demonstrate the strength of combined techniques in paternity testing.

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

A new scenario-based approach to damage detection using operational modal parameter estimates

NASA Astrophysics Data System (ADS)

Hansen, J. B.; Brincker, R.; López-Aenlle, M.; Overgaard, C. F.; Kloborg, K.

2017-09-01

In this paper a vibration-based damage localization and quantification method, based on natural frequencies and mode shapes, is presented. The proposed technique is inspired by a damage assessment methodology based solely on the sensitivity of mass-normalized experimental determined mode shapes. The present method differs by being based on modal data extracted by means of Operational Modal Analysis (OMA) combined with a reasonable Finite Element (FE) representation of the test structure and implemented in a scenario-based framework. Besides a review of the basic methodology this paper addresses fundamental theoretical as well as practical considerations which are crucial to the applicability of a given vibration-based damage assessment configuration. Lastly, the technique is demonstrated on an experimental test case using automated OMA. Both the numerical study as well as the experimental test case presented in this paper are restricted to perturbations concerning mass change.

A new hybrid case-based reasoning approach for medical diagnosis systems.

PubMed

Sharaf-El-Deen, Dina A; Moawad, Ibrahim F; Khalifa, M E

2014-02-01

Case-Based Reasoning (CBR) has been applied in many different medical applications. Due to the complexities and the diversities of this domain, most medical CBR systems become hybrid. Besides, the case adaptation process in CBR is often a challenging issue as it is traditionally carried out manually by domain experts. In this paper, a new hybrid case-based reasoning approach for medical diagnosis systems is proposed to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and also applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose breast cancer and thyroid diseases. The final results show that the proposed approach increases the diagnosing accuracy of the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer and thyroid diagnosis systems.

Applying knowledge compilation techniques to model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1991-01-01

Researchers in the area of knowledge compilation are developing general purpose techniques for improving the efficiency of knowledge-based systems. In this article, an attempt is made to define knowledge compilation, to characterize several classes of knowledge compilation techniques, and to illustrate how some of these techniques can be applied to improve the performance of model-based reasoning systems.

Case-based reasoning in design: An apologia

NASA Technical Reports Server (NTRS)

Pulaski, Kirt

1990-01-01

Three positions are presented and defended: the process of generating solutions in problem solving is viewable as a design task; case-based reasoning is a strong method of problem solving; and a synergism exists between case-based reasoning and design problem solving.

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.

PubMed

Ooi, Chia Huey; Chetty, Madhu; Teng, Shyh Wei

2006-06-23

Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gene expression-based tissue classification while improving accuracy at the same time. Surprisingly, this does not appear to be the case for all multiclass microarray datasets. The reason is that many feature selection techniques applied on microarray datasets are either rank-based and hence do not take into account correlations between genes, or are wrapper-based, which require high computational cost, and often yield difficult-to-reproduce results. In studies where correlations between genes are considered, attempts to establish the merit of the proposed techniques are hampered by evaluation procedures which are less than meticulous, resulting in overly optimistic estimates of accuracy. We present two realistically evaluated correlation-based feature selection techniques which incorporate, in addition to the two existing criteria involved in forming a predictor set (relevance and redundancy), a third criterion called the degree of differential prioritization (DDP). DDP functions as a parameter to strike the balance between relevance and redundancy, providing our techniques with the novel ability to differentially prioritize the optimization of relevance against redundancy (and vice versa). This ability proves useful in producing optimal classification accuracy while using reasonably small predictor set sizes for nine well-known multiclass microarray datasets. For multiclass microarray datasets, especially the GCM and NCI60 datasets, DDP enables our filter-based techniques to produce accuracies better than those reported in previous studies which employed similarly realistic evaluation procedures.

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

NASA Astrophysics Data System (ADS)

Xu, Bing; Liu, Liqun

To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

Improving real-time efficiency of case-based reasoning for medical diagnosis.

PubMed

Park, Yoon-Joo

2014-01-01

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. Some previous researches overcome this problem by clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new case-based reasoning method called the Clustering-Merging CBR (CM-CBR) which produces similar level of predictive performances than the conventional CBR with spending significantly less computational cost.

Combined Case of Blood-Injury-Injection Phobia and Social Phobia: Behavior Therapy Management and Effectiveness through Tilt Test

PubMed Central

Ferenidou, Fotini; Chalimourdas, Theodoros; Antonakis, Velissarios; Vaidakis, Nikolaos; Papadimitriou, Georgios

2012-01-01

The efficacy of behavior therapy based mainly on real-life exposure situations as well as applied tension was examined for a combined case of blood-injury-injection (BII) phobia and social anxiety disorder. Treatment involved 28 behavior therapy sessions, while applied tension technique was also described and practiced. The specific contribution of social skills techniques, fantasy, and real-life situations exposure was examined in a single case design. The subject was a 39-year-old male with anxiety symptoms when confronting an audience, as well as symptoms of the autonomic nervous system (bradycardia and syncope), which were better explained by BII. All self-report measures regarding fear, social phobia, and anxiety were reduced after behavior therapy and remained maintained at followup, while BII decreased further after applied tension techniques. The contribution of behavior therapy to the overall outcome of the case is considered significant for many reasons that are discussed in the pape. PMID:23304602

Cost-sensitive case-based reasoning using a genetic algorithm: application to medical diagnosis.

PubMed

Park, Yoon-Joo; Chun, Se-Hak; Kim, Byung-Chun

2011-02-01

The paper studies the new learning technique called cost-sensitive case-based reasoning (CSCBR) incorporating unequal misclassification cost into CBR model. Conventional CBR is now considered as a suitable technique for diagnosis, prognosis and prescription in medicine. However it lacks the ability to reflect asymmetric misclassification and often assumes that the cost of a positive diagnosis (an illness) as a negative one (no illness) is the same with that of the opposite situation. Thus, the objective of this research is to overcome the limitation of conventional CBR and encourage applying CBR to many real world medical cases associated with costs of asymmetric misclassification errors. The main idea involves adjusting the optimal cut-off classification point for classifying the absence or presence of diseases and the cut-off distance point for selecting optimal neighbors within search spaces based on similarity distribution. These steps are dynamically adapted to new target cases using a genetic algorithm. We apply this proposed method to five real medical datasets and compare the results with two other cost-sensitive learning methods-C5.0 and CART. Our finding shows that the total misclassification cost of CSCBR is lower than other cost-sensitive methods in many cases. Even though the genetic algorithm has limitations in terms of unstable results and over-fitting training data, CSCBR results with GA are better overall than those of other methods. Also the paired t-test results indicate that the total misclassification cost of CSCBR is significantly less than C5.0 and CART for several datasets. We have proposed a new CBR method called cost-sensitive case-based reasoning (CSCBR) that can incorporate unequal misclassification costs into CBR and optimize the number of neighbors dynamically using a genetic algorithm. It is meaningful not only for introducing the concept of cost-sensitive learning to CBR, but also for encouraging the use of CBR in the medical area. The result shows that the total misclassification costs of CSCBR do not increase in arithmetic progression as the cost of false absence increases arithmetically, thus it is cost-sensitive. We also show that total misclassification costs of CSCBR are the lowest among all methods in four datasets out of five and the result is statistically significant in many cases. The limitation of our proposed CSCBR is confined to classify binary cases for minimizing misclassification cost because our proposed CSCBR is originally designed to classify binary case. Our future work extends this method for multi-classification which can classify more than two groups. Copyright © 2010 Elsevier B.V. All rights reserved.

Supportive decision making at the point of care: refinement of a case-based reasoning application for use in nursing practice.

PubMed

DI Pietro, Tammie L; Doran, Diane M; McArthur, Gregory

2010-01-01

Variations in nursing care have been observed, affecting patient outcomes and quality of care. Case-based reasoners that benchmark for patient indicators can reduce variation through decision support. This study evaluated and validated a case-based reasoning application to establish benchmarks for nursing-sensitive patient outcomes of pain, fatigue, and toilet use, using patient characteristic variables for generating similar cases. Three graduate nursing students participated. Each ranked 25 patient cases using demographics of age, sex, diagnosis, and comorbidities against 10 patients from a database. Participant judgments of case similarity were compared with the case-based reasoning system. Feature weights for each indicator were adjusted to make the case-based reasoning system's similarity ranking correspond more closely to participant judgment. Small differences were noted between initial weights and weights generated from participants. For example, initial weight for comorbidities was 0.35, whereas weights generated by participants for pain, fatigue, and toilet use were 0.49, 0.42, and 0.48, respectively. For the same outcomes, the initial weight for sex was 0.15, but weights generated by the participants were 0.025, 0.002, and 0.000, respectively. Refinement of the case-based reasoning tool established valid benchmarks for patient outcomes in relation to participants and assisted in point-of-care decision making.

Similarity networks as a knowledge representation for space applications

NASA Technical Reports Server (NTRS)

Bailey, David; Thompson, Donna; Feinstein, Jerald

1987-01-01

Similarity networks are a powerful form of knowledge representation that are useful for many artificial intelligence applications. Similarity networks are used in applications ranging from information analysis and case based reasoning to machine learning and linking symbolic to neural processing. Strengths of similarity networks include simple construction, intuitive object storage, and flexible retrieval techniques that facilitate inferencing. Therefore, similarity networks provide great potential for space applications.

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents.

PubMed

Yu, Hongyang; Khan, Faisal; Veitch, Brian

2017-09-01

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation-based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source-to-source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry. © 2017 Society for Risk Analysis.

Dual-energy contrast-enhanced mammography.

PubMed

Travieso Aja, M M; Rodríguez Rodríguez, M; Alayón Hernández, S; Vega Benítez, V; Luzardo, O P

2014-01-01

The degree of vascularization in breast lesions is related to their malignancy. For this reason, functional diagnostic imaging techniques have become important in recent years. Dual-energy contrast-enhanced mammography is a new, apparently promising technique in breast cancer that provides information about the degree of vascularization of the lesion in addition to the morphological information provided by conventional mammography. This article describes the state of the art for dual-energy contrast-enhanced mammography. Based on 15 months' clinical experience, we illustrate this review with clinical cases that allow us to discuss the advantages and limitations of this technique. Copyright © 2014 SERAM. Published by Elsevier Espana. All rights reserved.

Articular dysfunction patterns in patients with mechanical neck pain: a clinical algorithm to guide specific mobilization and manipulation techniques.

PubMed

Dewitte, Vincent; Beernaert, Axel; Vanthillo, Bart; Barbe, Tom; Danneels, Lieven; Cagnie, Barbara

2014-02-01

In view of a didactical approach for teaching cervical mobilization and manipulation techniques to students as well as their use in daily practice, it is mandatory to acquire sound clinical reasoning to optimally apply advanced technical skills. The aim of this Masterclass is to present a clinical algorithm to guide (novice) therapists in their clinical reasoning to identify patients who are likely to respond to mobilization and/or manipulation. The presented clinical reasoning process is situated within the context of pain mechanisms and is narrowed to and applicable in patients with a dominant input pain mechanism. Based on key features in subjective and clinical examination, patients with mechanical nociceptive pain probably arising from articular structures can be categorized into specific articular dysfunction patterns. Pending on these patterns, specific mobilization and manipulation techniques are warranted. The proposed patterns are illustrated in 3 case studies. This clinical algorithm is the corollary of empirical expertise and is complemented by in-depth discussions and knowledge exchange with international colleagues. Consequently, it is intended that a carefully targeted approach contributes to an increase in specificity and safety in the use of cervical mobilizations and manipulation techniques as valuable adjuncts to other manual therapy modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integration of Optimal Scheduling with Case-Based Planning.

DTIC Science & Technology

1995-08-01

integrates Case-Based Reasoning (CBR) and Rule-Based Reasoning (RBR) systems. ’ Tachyon : A Constraint-Based Temporal Reasoning Model and Its...Implementation’ provides an overview of the Tachyon temporal’s reasoning system and discusses its possible applications. ’Dual-Use Applications of Tachyon : From...Force Structure Modeling to Manufacturing Scheduling’ discusses the application of Tachyon to real world problems, specifically military force deployment and manufacturing scheduling.

Nurses' reasoning process during care planning taking pressure ulcer prevention as an example. A think-aloud study.

PubMed

Funkesson, Kajsa Helena; Anbäcken, Els-Marie; Ek, Anna-Christina

2007-09-01

Nurses' clinical reasoning is of great importance for the delivery of safe and efficient care. Pressure ulcer prevention allows a variety of aspects within nursing to be viewed. The aim of this study was to describe both the process and the content of nurses' reasoning during care planning at different nursing homes, using pressure ulcer prevention as an example. A qualitative research design was chosen. Seven different nursing homes within one community were included. Eleven registered nurses were interviewed. The methods used were think-aloud technique, protocol analysis and qualitative content analysis. Client simulation illustrating transition was used. The case used for care planning was in three parts covering the transition from hospital until 3 weeks in the nursing home. Most nurses in this study conducted direct and indirect reasoning in a wide range of areas in connection with pressure ulcer prevention. The reasoning focused different parts of the nursing process depending on part of the case. Complex assertations as well as strategies aiming to reduce cognitive strain were rare. Nurses involved in direct nursing care held a broader reasoning than consultant nurses. Both explanations and actions based on older ideas and traditions occurred. Reasoning concerning pressure ulcer prevention while care planning was dominated by routine thinking. Knowing the person over a period of time made a more complex reasoning possible. The nurses' experience, knowledge together with how close to the elderly the nurses work seem to be important factors that affect the content of reasoning.

Knowledge acquisition for case-based reasoning systems

NASA Technical Reports Server (NTRS)

Riesbeck, Christopher K.

1988-01-01

Case-based reasoning (CBR) is a simple idea: solve new problems by adapting old solutions to similar problems. The CBR approach offers several potential advantages over rule-based reasoning: rules are not combined blindly in a search for solutions, solutions can be explained in terms of concrete examples, and performance can improve automatically as new problems are solved and added to the case library. Moving CBR for the university research environment to the real world requires smooth interfaces for getting knowledge from experts. Described are the basic elements of an interface for acquiring three basic bodies of knowledge that any case-based reasoner requires: the case library of problems and their solutions, the analysis rules that flesh out input problem specifications so that relevant cases can be retrieved, and the adaptation rules that adjust old solutions to fit new problems.

Case-based reasoning: The marriage of knowledge base and data base

NASA Technical Reports Server (NTRS)

Pulaski, Kirt; Casadaban, Cyprian

1988-01-01

The coupling of data and knowledge has a synergistic effect when building an intelligent data base. The goal is to integrate the data and knowledge almost to the point of indistinguishability, permitting them to be used interchangeably. Examples given in this paper suggest that Case-Based Reasoning is a more integrated way to link data and knowledge than pure rule-based reasoning.

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

PubMed

Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino

2009-06-18

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.

Propagating Resource Constraints Using Mutual Exclusion Reasoning

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Sanchez, Romeo; Do, Minh B.; Clancy, Daniel (Technical Monitor)

2001-01-01

One of the most recent techniques for propagating resource constraints in Constraint Based scheduling is Energy Constraint. This technique focuses in precedence based scheduling, where precedence relations are taken into account rather than the absolute position of activities. Although, this particular technique proved to be efficient on discrete unary resources, it provides only loose bounds for jobs using discrete multi-capacity resources. In this paper we show how mutual exclusion reasoning can be used to propagate time bounds for activities using discrete resources. We show that our technique based on critical path analysis and mutex reasoning is just as effective on unary resources, and also shows that it is more effective on multi-capacity resources, through both examples and empirical study.

Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique.

PubMed

Lee, Minhyun; Koo, Choongwan; Hong, Taehoon; Park, Hyo Seon

2014-04-15

For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation.

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

2001-01-01

The goal of this project was to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project combined case-based reasoning (CBR) and concept maps (CMaps) to develop methods for capturing, organizing, and interactively accessing records of experiences encapsulating the methods and rationale underlying expert aerospace design, in order to bring the captured knowledge to bear to support future reasoning. The project's results contribute both principles and methods for effective design-aiding systems that aid capture and access of useful design knowledge. The project has been guided by the tenets that design-aiding systems must: (1) Leverage a designer's knowledge, rather than attempting to replace it; (2) Be able to reflect different designers' differing conceptualizations of the design task, and to clarify those conceptualizations to others; (3) Include capabilities to capture information both by interactive knowledge modeling and during normal use; and (4) Integrate into normal designer tasks as naturally and unobtrusive as possible.

Do Expert Clinical Teachers Have a Shared Understanding of What Constitutes a Competent Reasoning Performance in Case-Based Teaching?

ERIC Educational Resources Information Center

Gauthier, Geneviève; Lajoie, Susanne P.

2014-01-01

To explore the assessment challenge related to case based learning we study how experienced clinical teachers--i.e., those who regularly teach and assess case-based learning--conceptualize the notion of competent reasoning performance for specific teaching cases. Through an in-depth qualitative case study of five expert teachers, we investigate…

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

PubMed Central

2017-01-01

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

PubMed

Al-Khatib, Ra'ed M; Rashid, Nur'Aini Abdul; Abdullah, Rosni

2011-08-01

The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

PubMed

Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

2017-10-21

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

Recent trends in reinforcement corrosion assessment using piezo sensors via electro mechanical impedance technique

NASA Astrophysics Data System (ADS)

Visalakshi, Talakokula; Bhalla, Suresh; Gupta, Ashok; Bhattacharjee, Bishwajit

2014-03-01

Reinforced concrete (RC) is an economical, versatile and successful construction material as it can be moulded into a variety of shapes and finishes. In most cases, it is durable and strong, performing well throughout its service life. However, in some cases, it does not perform adequately due to various reasons, one of which is the corrosion of the embedded steel bars used as reinforcement. . Although the electro-mechanical impedance (EMI) technique is well established for damage detection and quantification of civil, mechanical and aerospace structures, only limited studies have been reported of its application for rebar corrosion detection in RC structures. This paper presents the recent trends in corrosion assessment based on the model derived from the equivalent structural parameters extracted from the impedance spectrum of concrete-rebar system using the lead zirconate titanate (PZT) sensors via EMI technique.

TECHNIQUES FOR EFFECTIVE TEACHING.

ERIC Educational Resources Information Center

HASTINGS, GERALDINE; AND OTHERS

A COMPENDIUM OF WORKABLE AND REASONABLE TECHNIQUES TO PROVIDE TEACHERS WITH ALTERNATIVES IN SELECTING LEARNING EXPERIENCES IS PRESENTED. MATERIALS ARE DESIGNED TO AID TEACHERS AND LEARNERS IN ALL SUBJECT MATTER AREAS. TEACHING TECHNIQUES DESCRIBED ARE (1) THE CASE STUDY, (2) DISCUSSIONS SUCH AS SYMPOSIUM, COLLOQUIUM, BUZZ SESSIONS, AND…

Reasoning and Data Representation in a Health and Lifestyle Support System.

PubMed

Hanke, Sten; Kreiner, Karl; Kropf, Johannes; Scase, Marc; Gossy, Christian

2017-01-01

Case-based reasoning and data interpretation is an artificial intelligence approach that capitalizes on past experience to solve current problems and this can be used as a method for practical intelligent systems. Case-based data reasoning is able to provide decision support for experts and clinicians in health systems as well as lifestyle systems. In this project we were focusing on developing a solution for healthy ageing considering daily activities, nutrition as well as cognitive activities. The data analysis of the reasoner followed state of the art guidelines from clinical practice. Guidelines provide a general framework to guide clinicians, and require consequent background knowledge to become operational, which is precisely the kind of information recorded in practice cases; cases complement guidelines very well and helps to interpret them. It is expected that the interest in case-based reasoning systems in the health.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

Web-based unfolding cases: a strategy to enhance and evaluate clinical reasoning skills.

PubMed

Johnson, Gail; Flagler, Susan

2013-10-01

Clinical reasoning involves the use of both analytical and nonanalytical intuitive cognitive processes. Fostering student development of clinical reasoning skills and evaluating student performance in this cognitive arena can challenge educators. The use of Web-based unfolding cases is proposed as a strategy to address these challenges. Unfolding cases mimic real-life clinical situations by presenting only partial clinical information in sequential segments. Students receive immediate feedback after submitting a response to a given segment. The student's comparison of the desired and submitted responses provides information to enhance the development of clinical reasoning skills. Each student's set of case responses are saved for the instructor in an individual-student electronic file, providing a record of the student's knowledge and thinking processes for faculty evaluation. For the example case given, the approaches used to evaluate individual components of clinical reasoning are provided. Possible future uses of Web-based unfolding cases are described. Copyright 2013, SLACK Incorporated.

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

NASA Technical Reports Server (NTRS)

Poll, Scott; Iverson, David; Patterson-Hine, Ann

2003-01-01

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

The Identification of Reasons, Solutions, and Techniques Informing a Theory-Based Intervention Targeting Recreational Sports Participation.

PubMed

St Quinton, Tom; Brunton, Julie A

2018-06-01

This study is the 3rd piece of formative research utilizing the theory of planned behavior to inform the development of a behavior change intervention. Focus groups were used to identify reasons for and solutions to previously identified key beliefs in addition to potentially effective behavior change techniques. A purposive sample of 22 first-year undergraduate students (n = 8 men; M age  = 19.8 years, SD = 1.3 years) attending a university in the North of England was used. Focus groups were audio-recorded; recordings were transcribed verbatim, analyzed thematically, and coded for recurrent themes. The data revealed 14 reasons regarding enjoyment, 11 reasons for friends' approval, 11 reasons for friends' own participation, 14 reasons for the approval of family members, and 10 solutions to time constraints. Twelve distinct techniques were suggested to attend to these reasons and solutions. This qualitative research will be used to inform the development of a theory-based intervention to increase students' participation in university recreational sports.

Using computer aided case based reasoning to support clinical reasoning in community occupational therapy.

PubMed

Taylor, Bruce; Robertson, David; Wiratunga, Nirmalie; Craw, Susan; Mitchell, Dawn; Stewart, Elaine

2007-08-01

Community occupational therapists have long been involved in the provision of environmental control systems. Diverse electronic technologies with the potential to improve the health and quality of life of selected clients have developed rapidly in recent years. Occupational therapists employ clinical reasoning in order to determine the most appropriate technology to meet the needs of individual clients. This paper describes a number of the drivers that may increase the adoption of information and communication technologies in the occupational therapy profession. It outlines case based reasoning as understood in the domains of expert systems and knowledge management and presents the preliminary results of an ongoing investigation into the potential of a prototype computer aided case based reasoning tool to support the clinical reasoning of community occupational therapists in the process of assisting clients to choose home electronic assistive or smart house technology.

MapReduce in the Cloud: A Use Case Study for Efficient Co-Occurrence Processing of MEDLINE Annotations with MeSH.

PubMed

Kreuzthaler, Markus; Miñarro-Giménez, Jose Antonio; Schulz, Stefan

2016-01-01

Big data resources are difficult to process without a scaled hardware environment that is specifically adapted to the problem. The emergence of flexible cloud-based virtualization techniques promises solutions to this problem. This paper demonstrates how a billion of lines can be processed in a reasonable amount of time in a cloud-based environment. Our use case addresses the accumulation of concept co-occurrence data in MEDLINE annotation as a series of MapReduce jobs, which can be scaled and executed in the cloud. Besides showing an efficient way solving this problem, we generated an additional resource for the scientific community to be used for advanced text mining approaches.

Effects of a Case-Based Reasoning System on Student Performance in a Java Programming Course

ERIC Educational Resources Information Center

Schmidt, Cecil

2007-01-01

The purpose of this study was to determine if a case-based reasoning tool would improve a student's understanding of the complex concepts in a Java programming course. Subjects for the study were randomly assigned from two sections of an introductory Java programming course. Posttests were used to measure the effects of the case-based reasoning…

A Case-Based Reasoning Method with Rank Aggregation

NASA Astrophysics Data System (ADS)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

Elective tracheostomy in intensive care unit: Looking between techniques, a three cases report

PubMed Central

Ferraro, Fausto; Marullo, Lucia; d’Elia, Anna; Izzo, Giuseppe

2014-01-01

There is no optimal tracheostomy (TS) technique, proved to be the best. For this reason, operators’ skills, clinical anatomical and physio-pathological features of the patient should be considered as discriminating factors in the choice of percutaneous dilation tracheostomy (PDT) technique. This article includes reports of three cases of PDT: In the first case distance between jugular notch and the first tracheal ring was too long, the second case involving a patient with mild ectasia of the ascending aorta and aortic regurgitation with De Musset's sign with great risk of perioperative bleeding and a third case, of tracheomalacia with inflammatory stenosis at the 4th tracheal ring. All together, this case series describes how decisions were made by an experienced staff, in which the patient characteristics were assessed and techniques best suited for each case were implemented. PMID:24963186

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Monitoring progression of clinical reasoning skills during health sciences education using the case method - a qualitative observational study.

PubMed

Orban, Kristina; Ekelin, Maria; Edgren, Gudrun; Sandgren, Olof; Hovbrandt, Pia; Persson, Eva K

2017-09-11

Outcome- or competency-based education is well established in medical and health sciences education. Curricula are based on courses where students develop their competences and assessment is also usually course-based. Clinical reasoning is an important competence, and the aim of this study was to monitor and describe students' progression in professional clinical reasoning skills during health sciences education using observations of group discussions following the case method. In this qualitative study students from three different health education programmes were observed while discussing clinical cases in a modified Harvard case method session. A rubric with four dimensions - problem-solving process, disciplinary knowledge, character of discussion and communication - was used as an observational tool to identify clinical reasoning. A deductive content analysis was performed. The results revealed the students' transition over time from reasoning based strictly on theoretical knowledge to reasoning ability characterized by clinical considerations and experiences. Students who were approaching the end of their education immediately identified the most important problem and then focused on this in their discussion. Practice knowledge increased over time, which was seen as progression in the use of professional language, concepts, terms and the use of prior clinical experience. The character of the discussion evolved from theoretical considerations early in the education to clinical reasoning in later years. Communication within the groups was supportive and conducted with a professional tone. Our observations revealed progression in several aspects of students' clinical reasoning skills on a group level in their discussions of clinical cases. We suggest that the case method can be a useful tool in assessing quality in health sciences education.

Articular dysfunction patterns in patients with mechanical low back pain: A clinical algorithm to guide specific mobilization and manipulation techniques.

PubMed

Dewitte, V; Cagnie, B; Barbe, T; Beernaert, A; Vanthillo, B; Danneels, L

2015-06-01

Recent systematic reviews have demonstrated reasonable evidence that lumbar mobilization and manipulation techniques are beneficial. However, knowledge on optimal techniques and doses, and its clinical reasoning is currently lacking. To address this, a clinical algorithm is presented so as to guide therapists in their clinical reasoning to identify patients who are likely to respond to lumbar mobilization and/or manipulation and to direct appropriate technique selection. Key features in subjective and clinical examination suggestive of mechanical nociceptive pain probably arising from articular structures, can categorize patients into distinct articular dysfunction patterns. Based on these patterns, specific mobilization and manipulation techniques are suggested. This clinical algorithm is merely based on empirical clinical expertise and complemented through knowledge exchange between international colleagues. The added value of the proposed articular dysfunction patterns should be considered within a broader perspective. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Design of Product Collaborative Online Configuration Model

NASA Astrophysics Data System (ADS)

Wang, Xiaoguo; Zheng, Jin; Zeng, Qian

According to the actual needs of mass customization, the personalization of product and its collaborative design, the paper analyzes and studies the working mechanism of modular-based product configuration technology and puts forward an information model of modular product family. Combined with case-based reasoning techniques (CBR) and the constraint satisfaction problem solving techniques (CSP), we design and study the algorithm for product configuration, and analyze its time complexity. A car chassis is made as the application object, we provide a prototype system of online configuration. Taking advantage of this system, designers can make appropriate changes on the existing programs in accordance with the demand. This will accelerate all aspects of product development and shorten the product cycle. Also the system will provide a strong technical support for enterprises to improve their market competitiveness.

Case-based medical informatics

PubMed Central

Pantazi, Stefan V; Arocha, José F; Moehr, Jochen R

2004-01-01

Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. Summary Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately. PMID:15533257

The role of professional knowledge in case-based reasoning in practical ethics.

PubMed

Pinkus, Rosa Lynn; Gloeckner, Claire; Fortunato, Angela

2015-06-01

The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a general consensus that case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one's professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: (1) Experts in a research domain in bioengineering. (2) Novices in a research domain in bioengineering. (3) The non-research group--students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student's level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills.

The forced sound transmission of finite single leaf walls using a variational technique.

PubMed

Brunskog, Jonas

2012-09-01

The single wall is the simplest element of concern in building acoustics, but there still remain some open questions regarding the sound insulation of this simple case. The two main reasons for this are the effects on the excitation and sound radiation of the wall when it has a finite size, and the fact that the wave field in the wall is consisting of two types of waves, namely forced waves due to the exciting acoustic field, and free bending waves due to reflections in the boundary. The aim of the present paper is to derive simple analytical formulas for the forced part of the airborne sound insulation of a single homogeneous wall of finite size, using a variational technique based on the integral-differential equation of the fluid loaded wall. The so derived formulas are valid in the entire audible frequency range. The results are compared with full numerical calculations, measurements and alternative theory, with reasonable agreement.

Worked Examples Leads to Better Performance in Analyzing and Solving Real-Life Decision Cases

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2012-01-01

This study compared the impact of three types of case-based methods (worked example, faded worked example, and case-based reasoning) on preservice teachers' (n=71) decision making and reasoning related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three major…

Toward translational incremental similarity-based reasoning in breast cancer grading

NASA Astrophysics Data System (ADS)

Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir

2009-02-01

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.

Towards a Compositional SPIN

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Giannakopoulou, Dimitra

2006-01-01

This paper discusses our initial experience with introducing automated assume-guarantee verification based on learning in the SPIN tool. We believe that compositional verification techniques such as assume-guarantee reasoning could complement the state-reduction techniques that SPIN already supports, thus increasing the size of systems that SPIN can handle. We present a "light-weight" approach to evaluating the benefits of learning-based assume-guarantee reasoning in the context of SPIN: we turn our previous implementation of learning for the LTSA tool into a main program that externally invokes SPIN to provide the model checking-related answers. Despite its performance overheads (which mandate a future implementation within SPIN itself), this approach provides accurate information about the savings in memory. We have experimented with several versions of learning-based assume guarantee reasoning, including a novel heuristic introduced here for generating component assumptions when their environment is unavailable. We illustrate the benefits of learning-based assume-guarantee reasoning in SPIN through the example of a resource arbiter for a spacecraft. Keywords: assume-guarantee reasoning, model checking, learning.

A fuzzy case based reasoning tool for model based approach to rocket engine health monitoring

NASA Technical Reports Server (NTRS)

Krovvidy, Srinivas; Nolan, Adam; Hu, Yong-Lin; Wee, William G.

1992-01-01

In this system we develop a fuzzy case based reasoner that can build a case representation for several past anomalies detected, and we develop case retrieval methods that can be used to index a relevant case when a new problem (case) is presented using fuzzy sets. The choice of fuzzy sets is justified by the uncertain data. The new problem can be solved using knowledge of the model along with the old cases. This system can then be used to generalize the knowledge from previous cases and use this generalization to refine the existing model definition. This in turn can help to detect failures using the model based algorithms.

Short-term solar flare prediction using image-case-based reasoning

NASA Astrophysics Data System (ADS)

Liu, Jin-Fu; Li, Fei; Zhang, Huai-Peng; Yu, Da-Ren

2017-10-01

Solar flares strongly influence space weather and human activities, and their prediction is highly complex. The existing solutions such as data based approaches and model based approaches have a common shortcoming which is the lack of human engagement in the forecasting process. An image-case-based reasoning method is introduced to achieve this goal. The image case library is composed of SOHO/MDI longitudinal magnetograms, the images from which exhibit the maximum horizontal gradient, the length of the neutral line and the number of singular points that are extracted for retrieving similar image cases. Genetic optimization algorithms are employed for optimizing the weight assignment for image features and the number of similar image cases retrieved. Similar image cases and prediction results derived by majority voting for these similar image cases are output and shown to the forecaster in order to integrate his/her experience with the final prediction results. Experimental results demonstrate that the case-based reasoning approach has slightly better performance than other methods, and is more efficient with forecasts improved by humans.

History Matters: Incremental Ontology Reasoning Using Modules

NASA Astrophysics Data System (ADS)

Cuenca Grau, Bernardo; Halaschek-Wiener, Christian; Kazakov, Yevgeny

The development of ontologies involves continuous but relatively small modifications. Existing ontology reasoners, however, do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a technique for incremental reasoning—that is, reasoning that reuses information obtained from previous versions of an ontology—based on the notion of a module. Our technique does not depend on a particular reasoning calculus and thus can be used in combination with any reasoner. We have applied our results to incremental classification of OWL DL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

Properties of inductive reasoning.

PubMed

Heit, E

2000-12-01

This paper reviews the main psychological phenomena of inductive reasoning, covering 25 years of experimental and model-based research, in particular addressing four questions. First, what makes a case or event generalizable to other cases? Second, what makes a set of cases generalizable? Third, what makes a property or predicate projectable? Fourth, how do psychological models of induction address these results? The key results in inductive reasoning are outlined, and several recent models, including a new Bayesian account, are evaluated with respect to these results. In addition, future directions for experimental and model-based work are proposed.

Preferences of Teaching Methods and Techniques in Mathematics with Reasons

ERIC Educational Resources Information Center

Ünal, Menderes

2017-01-01

In this descriptive study, the goal was to determine teachers' preferred pedagogical methods and techniques in mathematics. Qualitative research methods were employed, primarily case studies. 40 teachers were randomly chosen from various secondary schools in Kirsehir during the 2015-2016 educational terms, and data were gathered via…

Application of artifical intelligence principles to the analysis of "crazy" speech.

PubMed

Garfield, D A; Rapp, C

1994-04-01

Artificial intelligence computer simulation methods can be used to investigate psychotic or "crazy" speech. Here, symbolic reasoning algorithms establish semantic networks that schematize speech. These semantic networks consist of two main structures: case frames and object taxonomies. Node-based reasoning rules apply to object taxonomies and pathway-based reasoning rules apply to case frames. Normal listeners may recognize speech as "crazy talk" based on violations of node- and pathway-based reasoning rules. In this article, three separate segments of schizophrenic speech illustrate violations of these rules. This artificial intelligence approach is compared and contrasted with other neurolinguistic approaches and is discussed as a conceptual link between neurobiological and psychodynamic understandings of psychopathology.

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

Does the Implantation Technique for Totally Implantable Venous Access Ports (TIVAPs) Influence Long-Term Outcome?

PubMed

Biacchi, Daniele; Sammartino, Paolo; Sibio, Simone; Accarpio, Fabio; Cardi, Maurizio; Sapienza, Paolo; De Cesare, Alessandro; Atta, Joseph Maher Fouad; Impagnatiello, Alessio; Di Giorgio, Angelo

2016-02-01

Totally implantable venous access ports (TIVAP) are eventually explanted for various reasons, related or unrelated to the implantation technique used. Having more information on long-term explantation would help improve placement techniques. From a series of 1572 cancer patients who had TIVAPs implanted in our center with the cutdown technique or Seldinger technique, we studied the 542 patients who returned to us to have their TIVAP explanted after 70 days or more. As outcome measures we distinguished between TIVAPs explanted for long-term complications (infection, catheter-, reservoir-, and patient-related complications) and TIVAPs no longer needed. Univariate and multivariate analyses were run to investigate the reasons for explantation and their possible correlation with implantation techniques. The most common reason for explantation was infection (47.6 %), followed by catheter-related (20.8 %), patient-related (14.7 %), and reservoir-related complications (4.7 %). In the remaining 12.2 % of cases, the TIVAP was explanted complication free after the planned treatments ended. Infection correlated closely with longer TIVAP use. Univariate and multivariate analyses identified the Seldinger technique as a major risk factor for venous thrombosis and catheter dislocation. The need for long-term TIVAP explantation in about one-third of cancer patients is related to the implantation techniques used.

The Effect of a Case-Based Reasoning Instructional Model on Korean High School Students' Awareness in Climate Change Unit

ERIC Educational Resources Information Center

Jeong, Jinwoo; Kim, Hyoungbum; Chae, Dong-hyun; Kim, Eunjeong

2014-01-01

The purpose of this study is to investigate the effects of the case-based reasoning instructional model on learning about climate change unit. Results suggest that students showed interest because it allowed them to find the solution to the problem and solve the problem for themselves by analogy from other cases such as crossword puzzles in an…

Bringing explicit insight into cognitive psychology features during clinical reasoning seminars: a prospective, controlled study.

PubMed

Nendaz, Mathieu R; Gut, Anne M; Louis-Simonet, Martine; Perrier, Arnaud; Vu, Nu V

2011-04-01

Facets of reasoning competence influenced by an explicit insight into cognitive psychology features during clinical reasoning seminars have not been specifically explored. This prospective, controlled study, conducted at the University of Geneva Faculty of Medicine, Switzerland, assessed the impact on sixth-year medical students' patient work-up of case-based reasoning seminars, bringing them explicit insight into cognitive aspects of their reasoning. Volunteer students registered for our three-month Internal Medicine elective were assigned to one of two training conditions: standard (control) or modified (intervention) case-based reasoning seminars. These seminars start with the patient's presenting complaint and the students must ask the tutor for additional clinical information to progress through case resolution. For this intervention, the tutors made each step explicit to students and encouraged self-reflection on their reasoning processes. At the end of their elective, students' performances were assessed through encounters with two standardized patients and chart write-ups. Twenty-nine students participated, providing a total of 58 encounters. The overall differences in accuracy of the final diagnosis given to the patient at the end of the encounter (control 63% vs intervention 74%, p = 0.53) and of the final diagnosis mentioned in the patient chart (61% vs 70%, p = 0.58) were not statistically significant. The students in the intervention group significantly more often listed the correct diagnosis among the differential diagnoses in their charts (75% vs 97%, p = 0.02). This case-based clinical reasoning seminar intervention, designed to bring students insight into cognitive features of their reasoning, improved aspects of diagnostic competence.

42 CFR 1003.109 - Notice of proposed determination.

Code of Federal Regulations, 2010 CFR

2010-10-01

... briefly describe the statistical sampling technique utilized by the Inspector General); (3) The reason why... statistical sampling in accordance with § 1003.133 in which case the notice shall describe those claims and...

Student-generated case reports.

PubMed

Good, Christopher J

2009-01-01

When students create teaching materials, learning can be enhanced. Therefore, a project was designed based on the traditional clinical case report and the chiropractic technique and principles curriculum at the University of Bridgeport College of Chiropractic. The objectives were to increase mastery in a clinical topic, increase awareness of different patient presentations and management options, and enhance information technology skills. Following lectures about the components of a case report and neurological reflexes related to visceral comorbidities and subluxation and joint dysfunction, students created a case report based on a template provided by the instructor. A survey gathered student perspectives on the exercise. More than 70% of the surveyed students felt the project was at least moderately helpful in improving understanding of a case report, the condition investigated, their clinical reasoning, and the ability to integrate information. Most felt that they improved their understanding of neurological reflexes, use of the literature, and the practice of evidence-based care. The majority believed that they identified weakness in knowledge, improved self-learning skills, and increased confidence in managing patients. Most enjoyed it at least somewhat and 70% agreed that the project should be continued. Many believed that they were better prepared for national boards and had improved their writing skills.

Overview of psychiatric ethics IV: the method of casuistry.

PubMed

Robertson, Michael; Ryan, Christopher; Walter, Garry

2007-08-01

The aim of this paper is to describe the method of ethical analysis known as casuistry and consider its merits as a basis of ethical deliberation in psychiatry. Casuistry approximates the legal arguments of common law. It examines ethical dilemmas by adopting a taxonomic approach to 'paradigm' cases, using a technique akin to that of normative analogical reasoning. Casuistry offers a useful method in ethical reasoning through providing a practical means of evaluating the merits of a particular course of action in a particular clinical situation. As a method ethical moral reasoning in psychiatry, casuistry suffers from a paucity of paradigm cases and its failure to fully contextualize ethical dilemmas by relying on common morality theory as its basis.

Trust-Guided Behavior Adaptation Using Case-Based Reasoning

DTIC Science & Technology

2015-08-01

the same behaviors were evaluated in each set. To account for this, the similarity function looks at the overlap between the two sets and ignores...interruptions would reduce the cost of case genera- tion. 6 Related Work Existing approaches for measuring inverse trust differ from our own in that...where a case- based reasoning system considers the reliability of a case’s source, also takes trust into account . Our work also has sim- ilarities

Analysis of Reasons for Failure of Surgery for Degenerative Disease of Lumbar Spine.

PubMed

Baranowska, Alicja; Baranowska, Joanna; Baranowski, Paweł

2016-03-23

In the aging society, there is a growing number of patients with advanced degenerative disease of the spine. These patients frequently require surgical treatment. This paper aims to analyse the reasons for failure of surgery for degenerative disease of the lumbar spine. Histories of patients operated on by one group of surgeons in the Neuroorthopaedic Department of "STOCER" in 2014 and 2015 due to degenerative disease of the lumbar spine were analysed retrospectively. Out of the cohort, patients who had undergone a revision surgery were selected for the study and divided into two groups: group A (60) of patients previously operated on in another centre and group B (47) of patients previously operated on in "STOCER". The reasons for failure of the surgery were analysed in detail based on history, physical examination, imaging studies and surgery reports. Surgery was performed in 601 patients, of whom 107 patients had been previously operated on. The most frequent reasons for revision surgery of the same motor segment were recurrent disc herniation, inadequate decompression and inappropriate surgical technique. In the group of patients who had implants inserted to stabilise the spine, the revision surgery in most cases was due to adjacent segment disease. Use of implants and spinal fusion is always associated with a risk of complications and is frequently independent of the surgeon. 2. In order to reduce the rate of revision surgeries, it is important to perform complete decompression and select an adequate surgical technique.

The Identification of Reasons, Solutions, and Techniques Informing a Theory-Based Intervention Targeting Recreational Sports Participation

ERIC Educational Resources Information Center

St Quinton, Tom; Brunton, Julie A.

2018-01-01

Purpose: This study is the 3rd piece of formative research utilizing the theory of planned behavior to inform the development of a behavior change intervention. Focus groups were used to identify reasons for and solutions to previously identified key beliefs in addition to potentially effective behavior change techniques. Method: A purposive…

Reasoning process characteristics in the diagnostic skills of beginner, competent, and expert dentists.

PubMed

Crespo, Kathleen E; Torres, José E; Recio, María E

2004-12-01

The purpose of this study was to evaluate qualitative differences in the diagnostic reasoning process at different developmental stages of expertise. A qualitative design was used to study cognitive processes that characterize the diagnosis of oral disease at the stages of beginner (five junior students who had passed the NBDE I), competent (five GPR first-year residents), and expert dentists (five general dentists with ten or more years of experience). Individually, each participant was asked to determine the diagnosis of an oral condition based on a written clinical case, using the think aloud technique and retrospective reports. A subsequent interview was conducted to obtain the participants' diagnostic process model and pathophysiology of the case. The analysis of the verbal protocols indicated that experts referred to the patient's sociomedical context more frequently, demonstrated better organization of ideas, could determine key clinical findings, and had an ability to plan for the search of pertinent information. Fewer diagnostic hypotheses were formulated by participants who used forward reasoning, independent of the stage of development. Beginners requested additional diagnostic aids (radiographs, laboratory tests) more frequently than the competent/expert dentists. Experts recalled typical experiences with patients, while competent/beginner dentists recalled information from didactic courses. Experts evidenced cognitive diagnostic schemas that integrate pathophysiology of disease, while competent and beginner participants had not achieved this integration. We conclude that expert performance is a combination of a knowledge base, reasoning skills, and an accumulation of experiences with patients that is qualitatively different from that of competent and beginner dentists. It is important for dental education to emphasize the teaching of cognitive processes and to incorporate a wide variety of clinical experiences in addition to the teaching of disciplinary content.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy.

PubMed

Liu, Rentao; Jiang, Jiping; Guo, Liang; Shi, Bin; Liu, Jie; Du, Zhaolin; Wang, Peng

2016-06-01

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.

Secondary School Students' Understanding of Science and Their Socioscientific Reasoning

NASA Astrophysics Data System (ADS)

Karahan, Engin; Roehrig, Gillian

2017-08-01

Research in socioscientific issue (SSI)-based interventions is relatively new (Sadler in Journal of Research in Science Teaching 41:513-536, 2004; Zeidler et al. in Journal of Research in Science Teaching 46:74-101, 2009), and there is a need for understanding more about the effects of SSI-based learning environments (Sadler in Journal of Research in Science Teaching 41:513-536, 2004). Lee and Witz (International Journal of Science Education 31:931-960, 2009) highlighted the need for detailed case studies that would focus on how students respond to teachers' practices of teaching SSI. This study presents case studies that investigated the development of secondary school students' science understanding and their socioscientific reasoning within SSI-based learning environments. A multiple case study with embedded units of analysis was implemented for this research because of the contextual differences for each case. The findings of the study revealed that students' understanding of science, including scientific method, social and cultural influences on science, and scientific bias, was strongly influenced by their experiences in SSI-based learning environments. Furthermore, multidimensional SSI-based science classes resulted in students having multiple reasoning modes, such as ethical and economic reasoning, compared to data-driven SSI-based science classes. In addition to portraying how participants presented complexity, perspectives, inquiry, and skepticism as aspects of socioscientific reasoning (Sadler et al. in Research in Science Education 37:371-391, 2007), this study proposes the inclusion of three additional aspects for the socioscientific reasoning theoretical construct: (1) identification of social domains affecting the SSI, (2) using cost and benefit analysis for evaluation of claims, and (3) understanding that SSIs and scientific studies around them are context-bound.

Newly developed liquid-based cytology. TACAS™: cytological appearance and HPV testing using liquid-based sample.

PubMed

Kubushiro, Kaneyuki; Taoka, Hideki; Sakurai, Nobuyuki; Yamamoto, Yasuhiro; Kurasaki, Akiko; Asakawa, Yasuyuki; Iwahara, Minoru; Takahashi, Kei

2011-09-01

Cell profiles determined by the thin-layer advanced cytology assay system (TACAS™), a liquid-based cytology technique newly developed in Japan, were analyzed in this study. Hybrid capture 2 (HC-2) was also performed using the liquid-based samples prepared by TACAS to ascertain its ability to detect human papillomavirus (HPV). Cell collection samples from uterine cervix were obtained from 359 patients and examined cytologically. A HC-2 assay for HPV was carried out in the cell specimens. All specimens were found to show background factors such as leukocytes. After excluding the 5 unsatisfactory cases from the total 354 cases, 82 cases (23.2%) were positive and 272 cases (76.8%) were negative for HPV. Cell specimens from 30 HPV-positive cases and 166 HPV-negative cases were subjected to 4 weeks of preservation at room temperature. Then, when subsequently re-assayed, 28 cases (93.3%) in the former group were found to be HPV positive and 164 cases (98.8%) in the latter group were found to be HPV negative. These results supported the excellent reproducibility of TACAS for HPV testing. A reasonable inference from the foregoing analysis is that TACAS may be distinguished from other liquid-based cytological approaches, such as ThinPrep and SurePath, in that it can retain the cell backgrounds. Furthermore, this study raises the possibility that cell specimens prepared using TACAS could be preserved for at least 4 weeks prior to carrying out a HC-2 assay for HPV.

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

PubMed

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Towards evidence-based practice in medical training: making evaluations more meaningful.

PubMed

Drescher, Uta; Warren, Fiona; Norton, Kingsley

2004-12-01

The evaluation of training is problematic and the evidence base inconclusive. This situation may arise for 2 main reasons: training is not understood as a complex intervention and, related to this, the evaluation methods applied are often overly simplistic. This paper makes the case for construing training, especially in the field of specialist medical education, as a complex intervention. It also selectively reviews the available literature in order to match evaluative techniques with the demonstrated complexity. Construing training as a complex intervention can provide a framework for selecting the most appropriate methodology to evaluate a given training intervention and to appraise the evidence base for training fairly, choosing from among both quantitative and qualitative approaches and applying measurement at multiple levels of training impact.

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

The continuous casting occupies a pivotal position in the iron and steel industry. The rough set theory and the CBR (case based reasoning, CBR) were combined in the research and implementation for the quality assurance of continuous casting billet to improve the efficiency and accuracy in determining the processing parameters. According to the continuous casting case, the object-oriented method was applied to express the continuous casting cases. The weights of the attributes were calculated by the algorithm which was based on the rough set theory and the retrieval mechanism for the continuous casting cases was designed. Some cases were adopted to test the retrieval mechanism, by analyzing the results, the law of the influence of the retrieval attributes on determining the processing parameters was revealed. A comprehensive evaluation model was established by using the attribute recognition theory. According to the features of the defects, different methods were adopted to describe the quality condition of the continuous casting billet. By using the system, the knowledge was not only inherited but also applied to adjust the processing parameters through the case based reasoning method as to assure the quality of the continuous casting and improve the intelligent level of the continuous casting.

Transformation based endorsement systems

NASA Technical Reports Server (NTRS)

Sudkamp, Thomas

1988-01-01

Evidential reasoning techniques classically represent support for a hypothesis by a numeric value or an evidential interval. The combination of support is performed by an arithmetic rule which often requires restrictions to be placed on the set of possibilities. These assumptions usually require the hypotheses to be exhausitive and mutually exclusive. Endorsement based classification systems represent support for the alternatives symbolically rather than numerically. A framework for constructing endorsement systems is presented in which transformations are defined to generate and update the knowledge base. The interaction of the knowledge base and transformations produces a non-monotonic reasoning system. Two endorsement based reasoning systems are presented to demonstrate the flexibility of the transformational approach for reasoning with ambiguous and inconsistent information.

Extending enterprise architecture modelling with business goals and requirements

NASA Astrophysics Data System (ADS)

Engelsman, Wilco; Quartel, Dick; Jonkers, Henk; van Sinderen, Marten

2011-02-01

The methods for enterprise architecture (EA), such as The Open Group Architecture Framework, acknowledge the importance of requirements modelling in the development of EAs. Modelling support is needed to specify, document, communicate and reason about goals and requirements. The current modelling techniques for EA focus on the products, services, processes and applications of an enterprise. In addition, techniques may be provided to describe structured requirements lists and use cases. Little support is available however for modelling the underlying motivation of EAs in terms of stakeholder concerns and the high-level goals that address these concerns. This article describes a language that supports the modelling of this motivation. The definition of the language is based on existing work on high-level goal and requirements modelling and is aligned with an existing standard for enterprise modelling: the ArchiMate language. Furthermore, the article illustrates how EA can benefit from analysis techniques from the requirements engineering domain.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

NASA Astrophysics Data System (ADS)

Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Clinical reasoning and case-based decision making: the fundamental challenge to veterinary educators.

PubMed

May, Stephen A

2013-01-01

Confusion about the nature of human reasoning and its appropriate application to patients has hampered veterinary students' development of these skills. Expertise is associated with greater ability to deploy pattern recognition (type 1 reasoning), which is aided by progressive development of data-driven, forward reasoning (in contrast to scientific, backward reasoning), analytical approaches that lead to schema acquisition. The associative nature of type 1 reasoning makes it prone to bias, particularly in the face of "cognitive miserliness," when clues that indicate the need for triangulation with an analytical approach are ignored. However, combined reasoning approaches, from the earliest stages, are more successful than one approach alone, so it is important that those involved in curricular design and delivery promote student understanding of reasoning generally, and the situations in which reasoning goes awry, and develop students' ability to reason safely and accurately whether presented with a familiar case or with a case that they have never seen before.

Characteristics of middle and upper tropospheric clouds as deduced from rawinsonde data

NASA Technical Reports Server (NTRS)

Starr, D. D. O.; Cox, S. K.

1982-01-01

The static environment of middle and upper tropospheric clouds is characterized. Computed relative humidity with respect to ice is used to diagnose the presence of cloud layer. The deduced seasonal mean cloud cover estimates based on this technique are shown to be reasonable. The cases are stratified by season and pressure thickness, and the dry static stability, vertical wind speed shear, and Richardson number are computed for three layers for each case. Mean values for each parameter are presented for each stratification and layer. The relative frequency of occurrence of various structures is presented for each stratification. The observed values of each parameter and the observed structure of each parameter are quite variable. Structures corresponding to any of a number of different conceptual models may be found. Moist adiabatic conditions are not commonly observed and the stratification based on thickness yields substantially different results for each group.

A dynamic case-based planning system for space station application

NASA Technical Reports Server (NTRS)

Oppacher, F.; Deugo, D.

1988-01-01

We are currently investigating the use of a case-based reasoning approach to develop a dynamic planning system. The dynamic planning system (DPS) is designed to perform resource management, i.e., to efficiently schedule tasks both with and without failed components. This approach deviates from related work on scheduling and on planning in AI in several aspects. In particular, an attempt is made to equip the planner with an ability to cope with a changing environment by dynamic replanning, to handle resource constraints and feedback, and to achieve some robustness and autonomy through plan learning by dynamic memory techniques. We briefly describe the proposed architecture of DPS and its four major components: the PLANNER, the plan EXECUTOR, the dynamic REPLANNER, and the plan EVALUATOR. The planner, which is implemented in Smalltalk, is being evaluated for use in connection with the Space Station Mobile Service System (MSS).

Case-Based Analogical Reasoning: A Pedagogical Tool for Promotion of Clinical Reasoning

ERIC Educational Resources Information Center

Speicher, Timothy E.; Bell, Alexandra; Kehrhahn, Marijke; Casa, Douglas J.

2012-01-01

Context: One of the most common instructional methods utilized to promote learning transfer in health profession education is examination of a single patient case. However, in non-healthcare settings this practice has shown to be less effective in promoting learning than the examination of multiple cases with cueing. Objective(s): The primary…

Development of an Expert System for Representing Procedural Knowledge

NASA Technical Reports Server (NTRS)

Georgeff, Michael P.; Lansky, Amy L.

1985-01-01

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Reflexive reasoning for distributed real-time systems

NASA Technical Reports Server (NTRS)

Goldstein, David

1994-01-01

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

A Hybrid Approach Using Case-Based Reasoning and Rule-Based Reasoning to Support Cancer Diagnosis: A Pilot Study.

PubMed

Saraiva, Renata M; Bezerra, João; Perkusich, Mirko; Almeida, Hyggo; Siebra, Clauirton

2015-01-01

Recently there has been an increasing interest in applying information technology to support the diagnosis of diseases such as cancer. In this paper, we present a hybrid approach using case-based reasoning (CBR) and rule-based reasoning (RBR) to support cancer diagnosis. We used symptoms, signs, and personal information from patients as inputs to our model. To form specialized diagnoses, we used rules to define the input factors' importance according to the patient's characteristics. The model's output presents the probability of the patient having a type of cancer. To carry out this research, we had the approval of the ethics committee at Napoleão Laureano Hospital, in João Pessoa, Brazil. To define our model's cases, we collected real patient data at Napoleão Laureano Hospital. To define our model's rules and weights, we researched specialized literature and interviewed health professional. To validate our model, we used K-fold cross validation with the data collected at Napoleão Laureano Hospital. The results showed that our approach is an effective CBR system to diagnose cancer.

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

NASA Astrophysics Data System (ADS)

Huang, H.; Vong, C. M.; Wong, P. K.

2010-05-01

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenance (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.

Infrahepatic vena cavocavostomy, a modification of the piggyback technique for liver transplantation.

PubMed

Khanmoradi, Kamran; Defaria, Werviston; Nishida, Seigo; Levi, David; Kato, Tomoaki; Moon, Jang; Selvaggi, Gennaro; Tzakis, Andreas

2009-05-01

We describe our experience with a modification of the piggyback (PB) technique for orthotopic liver transplantation in which the donor infrahepatic vena cava is used as the venous outflow tract. From May 1997 to January 2006, a total of 109 cases using this technique were performed in 101 patients. Collected data included recipient demographics and diagnosis, warm ischemia time, use of venovenous bypass or temporary portacaval shunt and complications related to the venous outflow and graft, and patient survival. Data were compared with the patients undergoing standard PB technique during the same period. The reasons for using the technique were grouped according to whether there was a problem with the recipient hepatic veins or a concern about the length or diameter of the donor suprahepatic vena cava. These included the presence of a transjugular intrahepatic portosystemic shunt (eight cases), retransplantation (22 cases), thin-walled, friable hepatic veins (32 cases), Budd-Chiari syndrome (two cases), domino liver procurement (six cases), reduced or split liver grafts (five cases), and graft inferior vena cava to recipient hepatic veins size discrepancy (34 cases). There was no graft loss. The warm ischemia time was 39.65 minutes compared with 37 minutes in the standard PB group. The long-term graft and patient survival rates were similar in the two groups. Infrahepatic vena cavocavostomy is a useful variation of the standard PB technique.

Working memory, reasoning, and expertise in medicine-insights into their relationship using functional neuroimaging.

PubMed

Hruska, Pam; Krigolson, Olav; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Hecker, Kent G

2016-12-01

Clinical reasoning is dependent upon working memory (WM). More precisely, during the clinical reasoning process stored information within long-term memory is brought into WM to facilitate the internal deliberation that affords a clinician the ability to reason through a case. In the present study, we examined the relationship between clinical reasoning and WM while participants read clinical cases with functional magnetic resonance imaging (fMRI). More specifically, we examined the impact of clinical case difficulty (easy, hard) and clinician level of expertise (2nd year medical students, senior gastroenterologists) on neural activity within regions of cortex associated with WM (i.e., the prefrontal cortex) during the reasoning process. fMRI was used to scan ten second-year medical students and ten practicing gastroenterologists while they reasoned through sixteen clinical cases [eight straight forward (easy) and eight complex (hard)] during a single 1-h scanning session. Within-group analyses contrasted the easy and hard cases which were then subsequently utilized for a between-group analysis to examine effects of expertise (novice > expert, expert > novice). Reading clinical cases evoked multiple neural activations in occipital, prefrontal, parietal, and temporal cortical regions in both groups. Importantly, increased activation in the prefrontal cortex in novices for both easy and hard clinical cases suggests novices utilize WM more so than experts during clinical reasoning. We found that clinician level of expertise elicited differential activation of regions of the human prefrontal cortex associated with WM during clinical reasoning. This suggests there is an important relationship between clinical reasoning and human WM. As such, we suggest future models of clinical reasoning take into account that the use of WM is not consistent throughout all clinical reasoning tasks, and that memory structure may be utilized differently based on level of expertise.

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

[Application of array-based comparative genomic hybridization technique in genetic analysis of patients with spontaneous abortion].

PubMed

Chu, Y; Wu, D; Hou, Q F; Huo, X D; Gao, Y; Wang, T; Wang, H D; Yang, Y L; Liao, S X

2016-08-25

To investigate the value of array-based comparative genomic hybridization (array-CGH) technique for the detection of chromosomal analysis of miscarried embryo, and to provide genetic counseling for couples with spontaneous abortion. Totally 382 patients who underwent miscarriage were enrolled in this study. All aborted tissues were analyzed with conventional cytogenetic karyotyping and array-CGH, respectively. Through genetic analysis, all of the 382 specimens were successfully analyzed by array-CGH (100.0%, 382/382), and the detection rate of chromosomal aberrations was 46.6% (178/382). However, conventional karyotype analysis was successfully performed in 281 cases (73.6%, 281/382), and 113 (40.2%, 113/281) were found with chromosomal aberrations. Of these 178 samples identified by array-CGH, 163 samples (91.6%, 163/178) were aneuploidy, 15 samples (8.4%, 15/178) were segmental deletion and (or) duplication cases. Four of 10 cases with small segmental deletion and duplication were validated to be transferred from their fathers or mathers who were carriers of submicroscopic reciprocal translocation. Of these 113 abnormal karyotypes founded by conventional karyotyping, 108 cases (95.6%, 108/113) were aneuploidy and 5 cases (4.4%, 5/113) had chromosome structural aberrations. Most array-CGH results were consistent with conventional karyotyping but with 3 cases of discrepancy, which included 2 cases of triploids, 1 case of low-level mosaicism that undetcted by array-CGH. Compared with conventional karyotyping, there is an increased detection rate of chromosomal abnormalities when array-CGH is used to analyse the products of conception, primarilly because of its sucess with nonviable tissues. It could be a first-line method to determine the reason of miscarrage with higher accuracy and sensitivity.

An advanced artificial intelligence tool for menu design.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-01-01

The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

CDMBE: A Case Description Model Based on Evidence

PubMed Central

Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

2015-01-01

By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users' ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model. PMID:26421006

Papilla and pontic area regeneration in patient with gingival smile: A clinical case

PubMed Central

Gómez-Meda, Ramón; Torres-Sanchez, Carlos; Mareque-Bueno, Santiago; Zufía-González, Juan; Gutierrez-Pérez, José-Luis

2018-01-01

Purpose Connective tissue grafts are widely documented as a predictable technique for treating Miller Class I and II recessions, as well as procedures in which soft tissue augmentation is required for aesthetic reasons. This article aims to explore the resolution of a clinical case with this type of problema. Clinical case This case describes a technique for reconstructing a pontic area and adjacent papilla by means of two consecutive connective tissue grafts. The first graft served to increase the amount of tissue in the horizontal direction, and the second promoted vertical reconstruction of the defect. Results and Conclusion In cases with aesthetic requirements, restorative intervention may be able to mask tissue loss, but it can hardly achieve optimal aesthetic results. Periodontal plastic surgery techniques can be used to achieve that ideal result. The clinician must diagnose conditions in order to select correct treatment regimen for each individual case. Key words:Papilla, gingival smile, pontic, restorative dentistry. PMID:29849978

A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management

NASA Astrophysics Data System (ADS)

Martin, Andreas; Emmenegger, Sandro; Hinkelmann, Knut; Thönssen, Barbara

2017-04-01

The accessibility of project knowledge obtained from experiences is an important and crucial issue in enterprises. This information need about project knowledge can be different from one person to another depending on the different roles he or she has. Therefore, a new ontology-based case-based reasoning (OBCBR) approach that utilises an enterprise ontology is introduced in this article to improve the accessibility of this project knowledge. Utilising an enterprise ontology improves the case-based reasoning (CBR) system through the systematic inclusion of enterprise-specific knowledge. This enterprise-specific knowledge is captured using the overall structure given by the enterprise ontology named ArchiMEO, which is a partial ontological realisation of the enterprise architecture framework (EAF) ArchiMate. This ontological representation, containing historical cases and specific enterprise domain knowledge, is applied in a new OBCBR approach. To support the different information needs of different stakeholders, this OBCBR approach has been built in such a way that different views, viewpoints, concerns and stakeholders can be considered. This is realised using a case viewpoint model derived from the ISO/IEC/IEEE 42010 standard. The introduced approach was implemented as a demonstrator and evaluated using an application case that has been elicited from a business partner in the Swiss research project.

Examining students' graduation issues using data mining techniques - The case of TEI of Athens

NASA Astrophysics Data System (ADS)

Chalaris, Manolis; Gritzalis, Stefanos; Maragoudakis, Manolis; Sgouropoulou, Cleo; Lykeridou, Katerina

2015-02-01

One of the major issues that Greek Higher Education Institutes face is the delayed completion of studies of their students. For example, in the case of the Technological Educational Institute of Athens, in the academic year 2012-2013, the percentage of graduates with a length of studies of more than 6 years was 53%. This "problem" becomes harder if we consider that according to the new legislation, the Greek Higher Education Institutes (HEI) must cut off access to the students who "linger" too long. This means that many of these graduates wouldn't be able to complete their studies. While many institutes have systems to quantify and report the length of studies of all graduates, far less attention is typically paid to each student's reason(s) for delayed graduation. In this paper, we focus on examining the question of why students delay in the completion of their studies using several data mining techniques. Through the application of data mining techniques new knowledge will be provided to the administration of a HEI that could be used for solving this problem. The data used in our case study come from a questionnaire distributed to graduates of the institute but also from educational data stored in the Institute's student database.

Cognition of an expert tackling an unfamiliar conceptual physics problem

NASA Astrophysics Data System (ADS)

Schuster, David; Undreiu, Adriana

2009-11-01

We have investigated and analyzed the cognition of an expert tackling a qualitative conceptual physics problem of an unfamiliar type. Our goal was to elucidate the detailed cognitive processes and knowledge elements involved, irrespective of final solution form, and consider implications for instruction. The basic but non-trivial problem was to find qualitatively the direction of acceleration of a pendulum bob at various stages of its motion, a problem originally studied by Reif and Allen. Methodology included interviews, introspection, retrospection and self-reported metacognition. Multiple facets of cognition were revealed, with different reasoning strategies used at different stages and for different points on the path. An account is given of the zigzag thinking paths and interplay of reasoning modes and schema elements involved. We interpret the cognitive processes in terms of theoretical concepts that emerged, namely: case-based, principle-based, experiential-intuitive and practical-heuristic reasoning; knowledge elements and schemata; activation; metacognition and epistemic framing. The complexity of cognition revealed in this case study contrasts with the tidy principle-based solutions we present to students. The pervasive role of schemata, case-based reasoning, practical heuristic strategies, and their interplay with physics principles is noteworthy, since these aspects of cognition are generally neither recognized nor taught. The schema/reasoning-mode perspective has direct application in science teaching, learning and problem-solving.

Intelligent design of permanent magnet synchronous motor based on CBR

NASA Astrophysics Data System (ADS)

Li, Cong; Fan, Beibei

2018-05-01

Aiming at many problems in the design process of Permanent magnet synchronous motor (PMSM), such as the complexity of design process, the over reliance on designers' experience and the lack of accumulation and inheritance of design knowledge, a design method of PMSM Based on CBR is proposed in order to solve those problems. In this paper, case-based reasoning (CBR) methods of cases similarity calculation is proposed for reasoning suitable initial scheme. This method could help designers, by referencing previous design cases, to make a conceptual PMSM solution quickly. The case retain process gives the system self-enrich function which will improve the design ability of the system with the continuous use of the system.

Plasma spectroscopy analysis technique based on optimization algorithms and spectral synthesis for arc-welding quality assurance.

PubMed

Mirapeix, J; Cobo, A; González, D A; López-Higuera, J M

2007-02-19

A new plasma spectroscopy analysis technique based on the generation of synthetic spectra by means of optimization processes is presented in this paper. The technique has been developed for its application in arc-welding quality assurance. The new approach has been checked through several experimental tests, yielding results in reasonably good agreement with the ones offered by the traditional spectroscopic analysis technique.

Partitioning and interfacial tracers for differentiating NAPL entrapment configuration: column-scale investigation.

PubMed

Dai, D; Barranco, F T; Illangasekare, T H

2001-12-15

Research on the use of partitioning and interfacial tracers has led to the development of techniques for estimating subsurface NAPL amount and NAPL-water interfacial area. Although these techniques have been utilized with some success at field sites, current application is limited largely to NAPL at residual saturation, such as for the case of post-remediation settings where mobile NAPL has been removed through product recovery. The goal of this study was to fundamentally evaluate partitioning and interfacial tracer behavior in controlled column-scale test cells for a range of entrapment configurations varying in NAPL saturation, with the results serving as a determinant of technique efficacy (and design protocol) for use with complexly distributed NAPLs, possibly at high saturation, in heterogeneous aquifers. Representative end members of the range of entrapment configurations observed under conditions of natural heterogeneity (an occurrence with residual NAPL saturation [discontinuous blobs] and an occurrence with high NAPL saturation [continuous free-phase LNAPL lens]) were evaluated. Study results indicated accurate prediction (using measured tracer retardation and equilibrium-based computational techniques) of NAPL amount and NAPL-water interfacial area for the case of residual NAPL saturation. For the high-saturation LNAPL lens, results indicated that NAPL-water interfacial area, but not NAPL amount (underpredicted by 35%), can be reasonably determined using conventional computation techniques. Underprediction of NAPL amount lead to an erroneous prediction of NAPL distribution, as indicated by the NAPL morphology index. In light of these results, careful consideration should be given to technique design and critical assumptions before applying equilibrium-based partitioning tracer methodology to settings where NAPLs are complexly entrapped, such as in naturally heterogeneous subsurface formations.

[Vertical reduction mammaplasty for gigantomastia with massive fibroadenomatosis: a case report].

PubMed

Schmid, N; De Greef, C; Calteux, N; Duhem, C; Faverly, D

2006-12-01

Vertical reduction mammaplasty is one of the most debated < short-scar > breast reduction technique. Advantages and drawbacks of the technique are discussed; most of the authors do not accept it as the technique of choice for high glandular resection weights. In our case report we achieve it for a resection weight up to two kilograms with an areolar transposition distance of more than ten centimetres. We show that it is reasonable to realize it dealing with gigantomastia. The massive fibroadenomatosis is observed following immunosuppressive treatment for kidney transplantation. Cyclosporine intake, even sporadic, is at the origin of the growth of these multiple, bilateral and large fibroadenomas. Drug-induced cytokines stimulate their development.

Ontology-Based Method for Fault Diagnosis of Loaders.

PubMed

Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-02-28

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Ontology-Based Method for Fault Diagnosis of Loaders

PubMed Central

Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-01-01

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study. PMID:29495646

Validating agent oriented methodology (AOM) for netlogo modelling and simulation

NASA Astrophysics Data System (ADS)

WaiShiang, Cheah; Nissom, Shane; YeeWai, Sim; Sharbini, Hamizan

2017-10-01

AOM (Agent Oriented Modeling) is a comprehensive and unified agent methodology for agent oriented software development. AOM methodology was proposed to aid developers with the introduction of technique, terminology, notation and guideline during agent systems development. Although AOM methodology is claimed to be capable of developing a complex real world system, its potential is yet to be realized and recognized by the mainstream software community and the adoption of AOM is still at its infancy. Among the reason is that there are not much case studies or success story of AOM. This paper presents two case studies on the adoption of AOM for individual based modelling and simulation. It demonstrate how the AOM is useful for epidemiology study and ecological study. Hence, it further validate the AOM in a qualitative manner.

Infrared thermographic detection of buried grave sites

NASA Astrophysics Data System (ADS)

Weil, Gary J.; Graf, Richard J.

1992-04-01

Since time began, people have been born and people have died. For a variety of reasons grave sites have had to be located and investigated. These reasons have included legal, criminal, religious, construction and even simple curiosity problems. Destructive testing methods such as shovels and backhoes, have traditionally been used to determine grave site locations in fields, under pavements, and behind hidden locations. These existing techniques are slow, inconvenient, dirty, destructive, visually obtrusive, irritating to relatives, explosive to the media and expensive. A new, nondestructive, non-contact technique, infrared thermography has been developed to address these problems. This paper will describe how infrared thermography works and will be illustrated by several case histories.

The hypospadias classification affected the surgical outcomes of staged oral mucosa graft urethroplasty in hypospadias reoperation: An observational study.

PubMed

Zheng, Dachao; Fu, Shi; Li, Wenji; Xie, Minkai; Guo, Jianhua; Yao, Haijun; Wang, Zhong

2017-11-01

The staged graft urethroplasty is a recommended technique for repairing complex hypospadias. This retrospective study aimed to investigate the outcomes of this technique in hypospadias patients undergoing reoperation and to analyze the underlying contributing factors including age, meatus location, and graft and suture type.We retrospectively analyzed 40 hypospadias patients undergoing reoperation who received a staged oral graft urethroplasty, including 15 buccal mucosal grafts and 25 lingual mucosal grafts. Median age at presentation was 18.5 years, and median follow-up was 17.5 months (range 8-30 months). The patients were classified according to their original meatus location.Twenty-five complications developed in 12 of 40 (30%) cases, including 6 fistulas (15%), 7 infections (17.5%), 9 cases of glans dehiscence (22.5%), and 3 cases of stenosis (7.5%). There was no significant difference in the overall complication rates between prepuberty and postpuberty groups. In addition, no significant difference in complications was found between the 2 graft techniques. The complications were significantly higher in the original perineal type compared with the original penoscrotal type (7/10 vs 5/30, P = .0031). Seven patients who originally had perineal hypospadias developed multiple complications.Based on this study, the staged graft urethroplasty is an effective technique in reoperative hypospadias repairs with reasonable complication risk. The hypospadias classification affects the surgical outcomes. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2010 CFR

2010-01-01

... fuels other than biodiesel blends and biomass-based diesel blends, you must possess a reasonable basis... the fuel, and in the case of biomass-based diesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biomass-based diesel contained in the...

A personalized health-monitoring system for elderly by combining rules and case-based reasoning.

PubMed

Ahmed, Mobyen Uddin

2015-01-01

Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly's medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

Case-based retrieval framework for gene expression data.

PubMed

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

2015-01-01

The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

Hybrid glowworm swarm optimization for task scheduling in the cloud environment

NASA Astrophysics Data System (ADS)

Zhou, Jing; Dong, Shoubin

2018-06-01

In recent years many heuristic algorithms have been proposed to solve task scheduling problems in the cloud environment owing to their optimization capability. This article proposes a hybrid glowworm swarm optimization (HGSO) based on glowworm swarm optimization (GSO), which uses a technique of evolutionary computation, a strategy of quantum behaviour based on the principle of neighbourhood, offspring production and random walk, to achieve more efficient scheduling with reasonable scheduling costs. The proposed HGSO reduces the redundant computation and the dependence on the initialization of GSO, accelerates the convergence and more easily escapes from local optima. The conducted experiments and statistical analysis showed that in most cases the proposed HGSO algorithm outperformed previous heuristic algorithms to deal with independent tasks.

CABINS: Case-based interactive scheduler

NASA Technical Reports Server (NTRS)

Miyashita, Kazuo; Sycara, Katia

1992-01-01

In this paper we discuss the need for interactive factory schedule repair and improvement, and we identify case-based reasoning (CBR) as an appropriate methodology. Case-based reasoning is the problem solving paradigm that relies on a memory for past problem solving experiences (cases) to guide current problem solving. Cases similar to the current case are retrieved from the case memory, and similarities and differences of the current case to past cases are identified. Then a best case is selected, and its repair plan is adapted to fit the current problem description. If a repair solution fails, an explanation for the failure is stored along with the case in memory, so that the user can avoid repeating similar failures in the future. So far we have identified a number of repair strategies and tactics for factory scheduling and have implemented a part of our approach in a prototype system, called CABINS. As a future work, we are going to scale up CABINS to evaluate its usefulness in a real manufacturing environment.

Developing integrated clinical reasoning competencies in dental students using scaffolded case-based learning - empirical evidence.

PubMed

Postma, T C; White, J G

2016-08-01

This study provides empirical evidence of the development of integrated clinical reasoning in the discipline-based School of Dentistry, University of Pretoria, South Africa. Students were exposed to case-based learning in comprehensive patient care (CPC) in the preclinical year of study, scaffolded by means of the four-component instructional design model for complex learning. Progress test scores of third- to fifth-year dental students, who received case-based teaching and learning in the third year (2009-2011), were compared to the scores of preceding fourth- and fifth-year cohorts. These fourth- and fifth-year cohorts received content-based teaching concurrently with their clinical training in CPC. The progress test consisted of a complex case study and 32 MCQs on tracer conditions. Students had to gather the necessary information and had to make diagnostic and treatment-planning decisions. Preclinical students who participated in the case-based teaching and learning achieved similar scores compared to final-year students who received lecture-based teaching and learning. Final-year students who participated in the case-based learning made three more correct clinical decisions per student, compared to those who received content-based teaching. Students struggled more with treatment-planning than with diagnostic decisions. The scaffolded case-based learning appears to contribute to accurate clinical decisions when compared to lecture-based teaching. It is suggested that the development of integrated reasoning competencies starts as early as possible in a dental curriculum, perhaps even in the preclinical year of study. Treatment-planning should receive particular attention. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Cellular automatons applied to gas dynamic problems

NASA Technical Reports Server (NTRS)

Long, Lyle N.; Coopersmith, Robert M.; Mclachlan, B. G.

1987-01-01

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Case-Based Policy and Goal Recognition

DTIC Science & Technology

2015-09-30

or noisy. Ontanón et al. [8] use case-based reasoning (CBR) to model human driving vehicle control behaviors and skill level to reduce teen crash...Snodgrass, S., Bonfiglio, D., Winston, F.K., McDonald, C., Gonzalez, A.J.: Case-based prediction of teen driver behavior and skill. In: Pro- ceedings

Incremental Query Rewriting with Resolution

NASA Astrophysics Data System (ADS)

Riazanov, Alexandre; Aragão, Marcelo A. T.

We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a resolution-based first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent translation of these schematic answers to SQL queries which are evaluated using a conventional relational DBMS. We call our method incremental query rewriting, because an original semantic query is rewritten into a (potentially infinite) series of SQL queries. In this chapter, we outline the main idea of our technique - using abstractions of databases and constrained clauses for deriving schematic answers, and provide completeness and soundness proofs to justify the applicability of this technique to the case of resolution for FOL without equality. The proposed method can be directly used with regular RDBs, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, H.; Vong, C. M.; Wong, P. K.

2010-05-21

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenancemore » (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.« less

Why do clinicians choose the therapies and techniques they do? Exploring clinical decision-making via treatment selections in dysphagia practice.

PubMed

McCurtin, Arlene; Healy, Chiara

2017-02-01

Speech-language pathologists (SLPs) are assumed to use evidence-based practice to inform treatment decisions. However, the reasoning underpinning treatment selections is not well known. Understanding why SLPs choose the treatments they do may be clarified by exploring the reasoning tied to specific treatments such as dysphagia interventions. An electronic survey methodology was utilised. Participants were accessed via the gatekeepers of two national dysphagia special interest groups representing adult and paediatric populations. Information was elicited on the dysphagia therapies and techniques used and on the reasoning for using/not using therapies. Data was analysed using descriptive and non-parametric statistics. The survey had a 74.8% response rate (n = 116). Consensus in both treatment selections and reasoning supporting treatment decisions was evident. Three favoured interventions (texture modification, thickening liquids, positioning changes) were identified. The reasoning supporting treatment choices centred primarily on client suitability and clinician knowledge. Knowledge reflected both absent knowledge (e.g. training) and accumulated knowledge (clinical experience). Dysphagia practice appears highly-defined, being characterised by group consensus regarding both preferred treatments and the reasoning underpinning treatment selections. Treatment selections are based on two core criteria: client suitability and the SLPs experience/knowledge. Explicit scientific reasoning is less influential than practice-centric influences.

Improving end of life care: an information systems approach to reducing medical errors.

PubMed

Tamang, S; Kopec, D; Shagas, G; Levy, K

2005-01-01

Chronic and terminally ill patients are disproportionately affected by medical errors. In addition, the elderly suffer more preventable adverse events than younger patients. Targeting system wide "error-reducing" reforms to vulnerable populations can significantly reduce the incidence and prevalence of human error in medical practice. Recent developments in health informatics, particularly the application of artificial intelligence (AI) techniques such as data mining, neural networks, and case-based reasoning (CBR), presents tremendous opportunities for mitigating error in disease diagnosis and patient management. Additionally, the ubiquity of the Internet creates the possibility of an almost ideal network for the dissemination of medical information. We explore the capacity and limitations of web-based palliative information systems (IS) to transform the delivery of care, streamline processes and improve the efficiency and appropriateness of medical treatment. As a result, medical error(s) that occur with patients dealing with severe, chronic illness and the frail elderly can be reduced.The palliative model grew out of the need for pain relief and comfort measures for patients diagnosed with cancer. Applied definitions of palliative care extend this convention, but there is no widely accepted definition. This research will discuss the development life cycle of two palliative information systems: the CONFER QOLP management information system (MIS), currently used by a community-based palliative care program in Brooklyn, New York, and the CAREN case-based reasoning prototype. CONFER is a web platform based on the idea of "eCare". CONFER uses XML (extensible mark-up language), a W3C-endorced standard mark up to define systems data. The second system, CAREN, is a CBR prototype designed for palliative care patients in the cancer trajectory. CBR is a technique, which tries to exploit the similarities of two situations and match decision-making to the best-known precedent cases. The prototype uses the opensource CASPIAN shell developed by the University of Aberystwyth, Wales and is available by anonymous FTP. We will discuss and analyze the preliminary results we have obtained using this CBR tool. Our research suggests that automated information systems can be used to improve the quality of care at the end of life and disseminate expert level 'know how' to palliative care clinicians. We will present how our CBR prototype can be successfully deployed, capable of securely transferring information using a Secure File Transfer Protocol (SFTP) and using a JAVA CBR engine.

Comparison of ethical judgments exhibited by clients and ethics consultants in Japan.

PubMed

Nagao, Noriko; Kadooka, Yasuhiro; Asai, Atsushi

2014-03-04

Healthcare professionals must make decisions for patients based on ethical considerations. However, they rely on clinical ethics consultations (CEC) to review ethical justifications of their decisions. CEC consultants support the cases reviewed and guide medical care. When both healthcare professionals and CEC consultants face ethical problems in medical care, how is their judgment derived? How do medical judgments differ from the ethical considerations of CECs? This study examines CECs in Japan to identify differences in the ethical judgment of clients and CEC consultants. The CEC request and response documents of all 60 cases reviewed across Japan between October 2006 and the end of October 2011 were classified in terms of the presence of decisional capacity in the patient. We conducted a qualitative content analysis of the differences in reasoning between client and CEC consultants. Reasoned judgments were verified in individual cases to classify the similarities or differences of opinion between CEC clients and teams. As the result of classification of the decisional capacity and the difference of opinion regarding medical care, the most frequent category was 25 cases (41.7%) of "uncertain decisional capacity," and 23 cases (38.3%) of "withholding of decision-making." A chi-square analysis was performed on presence of decisional capacity and agreement in decision-making, yielding a statistically significant difference (p < 0.05). The CEC consultants' reasoning was based on "patient's preference was ambiguous," "validity of family as a surrogate," "estimation of patient preference," and "patient's best interest," whereas the CEC client's reasoning was based on "consistent family preference was shown/not shown" and "appropriate therapeutic methods to manage patient safety." Differences in opinions were found in cases classified according to decisional capacity. Furthermore, the reasoning behind judgments differed between CEC clients and CEC consultants. The reasoning of CEC consultants was critical and reflective, while for clients it was situational and pragmatic.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Design a Fuzzy Rule-based Expert System to Aid Earlier Diagnosis of Gastric Cancer.

PubMed

Safdari, Reza; Arpanahi, Hadi Kazemi; Langarizadeh, Mostafa; Ghazisaiedi, Marjan; Dargahi, Hossein; Zendehdel, Kazem

2018-01-01

Screening and health check-up programs are most important sanitary priorities, that should be undertaken to control dangerous diseases such as gastric cancer that affected by different factors. More than 50% of gastric cancer diagnoses are made during the advanced stage. Currently, there is no systematic approach for early diagnosis of gastric cancer. to develop a fuzzy expert system that can identify gastric cancer risk levels in individuals. This system was implemented in MATLAB software, Mamdani inference technique applied to simulate reasoning of experts in the field, a total of 67 fuzzy rules extracted as a rule-base based on medical expert's opinion. 50 case scenarios were used to evaluate the system, the information of case reports is given to the system to find risk level of each case report then obtained results were compared with expert's diagnosis. Results revealed that sensitivity was 92.1% and the specificity was 83.1%. The results show that is possible to develop a system that can identify High risk individuals for gastric cancer. The system can lead to earlier diagnosis, this may facilitate early treatment and reduce gastric cancer mortality rate.

Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations: Translational controller results

NASA Technical Reports Server (NTRS)

Jani, Yashvant

1992-01-01

The reinforcement learning techniques developed at Ames Research Center are being applied to proximity and docking operations using the Shuttle and Solar Maximum Mission (SMM) satellite simulation. In utilizing these fuzzy learning techniques, we also use the Approximate Reasoning based Intelligent Control (ARIC) architecture, and so we use two terms interchangeable to imply the same. This activity is carried out in the Software Technology Laboratory utilizing the Orbital Operations Simulator (OOS). This report is the deliverable D3 in our project activity and provides the test results of the fuzzy learning translational controller. This report is organized in six sections. Based on our experience and analysis with the attitude controller, we have modified the basic configuration of the reinforcement learning algorithm in ARIC as described in section 2. The shuttle translational controller and its implementation in fuzzy learning architecture is described in section 3. Two test cases that we have performed are described in section 4. Our results and conclusions are discussed in section 5, and section 6 provides future plans and summary for the project.

Endoscopic resection of subepithelial tumors.

PubMed

Schmidt, Arthur; Bauder, Markus; Riecken, Bettina; Caca, Karel

2014-12-16

Management of subepithelial tumors (SETs) remains challenging. Endoscopic ultrasound (EUS) has improved differential diagnosis of these tumors but a definitive diagnosis on EUS findings alone can be achieved in the minority of cases. Complete endoscopic resection may provide a reasonable approach for tissue acquisition and may also be therapeutic in case of malignant lesions. Small SET restricted to the submucosa can be removed with established basic resection techniques. However, resection of SET arising from deeper layers of the gastrointestinal wall requires advanced endoscopic methods and harbours the risk of perforation. Innovative techniques such as submucosal tunneling and full thickness resection have expanded the frontiers of endoscopic therapy in the past years. This review will give an overview about endoscopic resection techniques of SET with a focus on novel methods.

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

A prototype case-based reasoning human assistant for space crew assessment and mission management

NASA Technical Reports Server (NTRS)

Owen, Robert B.; Holland, Albert W.; Wood, Joanna

1993-01-01

We present a prototype human assistant system for space crew assessment and mission management. Our system is based on case episodes from American and Russian space missions and analog environments such as polar stations and undersea habitats. The general domain of small groups in isolated and confined environments represents a near ideal application area for case-based reasoning (CBR) - there are few reliable rules to follow, and most domain knowledge is in the form of cases. We define the problem domain and outline a unique knowledge representation system driven by conflict and communication triggers. The prototype system is able to represent, index, and retrieve case studies of human performance. We index by social, behavioral, and environmental factors. We present the problem domain, our current implementation, our research approach for an operational system, and prototype performance and results.

White spots on enamel: treatment protocol by superficial or deep infiltration (part 2).

PubMed

Attal, Jean-Pierre; Atlan, Anthony; Denis, Maud; Vennat, Elsa; Tirlet, Gilles

2014-03-01

In this 2nd part, the current treatment of white spot lesions by erosion/infiltration is presented, beginning with a reminder of the principle of superficial infiltration, which enables most early carious lesions, fluorosis and post-traumatic lesions to be treated. However, this technique has met with frequent failures in cases of MIH or deep lesions of traumatic origin or those associated with fluorosis. For this reason a new deep infiltration technique is proposed: thanks to its global treatment concept, this enables all white spots to be treated. The place of whitening in these treatment options is discussed, with explanations of the main reasons for its failures. Copyright © 2014 CEO. Published by Elsevier Masson SAS. All rights reserved.

[Teaching of clinical reasoning to medical students using prototypical clinical cases].

PubMed

Montaldo L, Gustavo; Herskovic L, Pedro

2013-07-01

Clinical reasoning is the most important competente in the training process of a physician. To develop a method for teaching clinical reasoning based on prototypes of clinical cases. The study was conducted on sixty-four third year medical students. The study and control groups attended lectures and tutorial sessions with patients. The study group attended additionally discussion seminars of prototypical clinical cases. A clinical reasoning test was applied at the start and end of the learning period to both groups. At the end of the study, the opinions of students of the study group were collected in a focus group. After the learning period, both groups significantly increased their clinical reasoning skills. However, the improvement in the study group was more than double than that of the control group. The absolute improvement in the study group was 30.9%. Students interviewed in the focus group were unanimous in expressing their satisfaction in each and every aspect discussed. The teaching of clinical reasoning to third year medical students by means of pattern recognition in seminars with clinical cases improved significantly their skills.

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

ERIC Educational Resources Information Center

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

[Gastric band erosion: Alternative management].

PubMed

Echaverry-Navarrete, Denis José; Maldonado-Vázquez, Angélica; Cortes-Romano, Pablo; Cabrera-Jardines, Ricardo; Mondragón-Pinzón, Erwin Eduardo; Castillo-González, Federico Armando

2015-01-01

Obesity is a public health problem, for which the prevalence has increased worldwide at an alarming rate, affecting 1.7 billion people in the world. To describe the technique employed in incomplete penetration of gastric band where endoscopic management and/or primary closure is not feasible. Laparoscopic removal of gastric band was performed in five patients with incomplete penetrance using Foley catheterization in the perforation site that could lead to the development of a gastro-cutaneous fistula. The cases presented include a leak that required surgical lavage with satisfactory outcome, and one patient developed stenosis 3 years after surgical management, which was resolved endoscopically. In all cases, the penetration site closed spontaneously. Gastric band erosion has been reported in 3.4% of cases. The reason for inserting a catheter is to create a controlled gastro-cutaneous fistula, allowing spontaneous closure. Various techniques have been described: the totally endoscopic, hybrid techniques (endoscopic/laparoscopic) and completely laparoscopic. A technique is described here that is useful and successful in cases where the above-described treatments are not viable. Copyright © 2015. Published by Masson Doyma México S.A.

Understanding and Evaluating Assurance Cases

NASA Technical Reports Server (NTRS)

Rushby, John; Xu, Xidong; Rangarajan, Murali; Weaver, Thomas L.

2015-01-01

Assurance cases are a method for providing assurance for a system by giving an argument to justify a claim about the system, based on evidence about its design, development, and tested behavior. In comparison with assurance based on guidelines or standards (which essentially specify only the evidence to be produced), the chief novelty in assurance cases is provision of an explicit argument. In principle, this can allow assurance cases to be more finely tuned to the specific circumstances of the system, and more agile than guidelines in adapting to new techniques and applications. The first part of this report (Sections 1-4) provides an introduction to assurance cases. Although this material should be accessible to all those with an interest in these topics, the examples focus on software for airborne systems, traditionally assured using the DO-178C guidelines and its predecessors. A brief survey of some existing assurance cases is provided in Section 5. The second part (Section 6) considers the criteria, methods, and tools that may be used to evaluate whether an assurance case provides sufficient confidence that a particular system or service is fit for its intended use. An assurance case cannot provide unequivocal "proof" for its claim, so much of the discussion focuses on the interpretation of such less-than-definitive arguments, and on methods to counteract confirmation bias and other fallibilities in human reasoning.

Constraint reasoning in deep biomedical models.

PubMed

Cruz, Jorge; Barahona, Pedro

2005-05-01

Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. The methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. The results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. The main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.

Can Tauc plot extrapolation be used for direct-band-gap semiconductor nanocrystals?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Y., E-mail: yu.feng@unsw.edu.au; Lin, S.; Huang, S.

Despite that Tauc plot extrapolation has been widely adopted for extracting bandgap energies of semiconductors, there is a lack of theoretical support for applying it to nanocrystals. In this paper, direct-allowed optical transitions in semiconductor nanocrystals have been formulated based on a purely theoretical approach. This result reveals a size-dependant transition of the power factor used in Tauc plot, increasing from one half used in the 3D bulk case to one in the 0D case. This size-dependant intermediate value of power factor allows a better extrapolation of measured absorption data. Being a material characterization technique, the generalized Tauc extrapolation givesmore » a more reasonable and accurate acquisition of the intrinsic bandgap, while the unjustified purpose of extrapolating any elevated bandgap caused by quantum confinement is shown to be incorrect.« less

Is there a role for assent or dissent in animal research?

PubMed

Kantin, Holly; Wendler, David

2015-10-01

Current regulations and widely accepted principles for animal research focus on minimizing the burdens and harms of research on animals. However, these regulations and principles do not consider a possible role for assent or dissent in animal research. Should investigators solicit the assent or respect the dissent of animals who are used in research, and, if so, under what circumstances? In this article we pursue this question and outline the relevant issues that bear on the answer. We distinguish two general reasons for respecting the preferences of research participants regarding whether they participate in research-welfare-based reasons and agency-based reasons. We argue that there are welfare-based reasons for researchers to consider, and in some cases respect, the dissent of all animals used in research. After providing a brief account of the nature of agency-based reasons, we argue that there is good reason to think that these reasons apply to at least chimpanzees. We argue that there is an additional reason for researchers to respect the dissent-and, when possible, solicit the assent-of any animal to whom agency-based reasons apply.

Longitudinal Assessment of Progress in Reasoning Capacity and Relation with Self-Estimation of Knowledge Base

ERIC Educational Resources Information Center

Collard, Anne; Mélot, France; Bourguignon, Jean-Pierre

2015-01-01

The aim of the study was to investigate progress in reasoning capacity and knowledge base appraisal in a longitudinal analysis of data from summative evaluation throughout a medical problem-based learning curriculum. The scores in multidisciplinary discussion of a clinical case and multiple choice questionnaires (MCQs) were studied longitudinally…

Intelligent agents for adaptive security market surveillance

NASA Astrophysics Data System (ADS)

Chen, Kun; Li, Xin; Xu, Baoxun; Yan, Jiaqi; Wang, Huaiqing

2017-05-01

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.

Current genetic methodologies in the identification of disaster victims and in forensic analysis.

PubMed

Ziętkiewicz, Ewa; Witt, Magdalena; Daca, Patrycja; Zebracka-Gala, Jadwiga; Goniewicz, Mariusz; Jarząb, Barbara; Witt, Michał

2012-02-01

This review presents the basic problems and currently available molecular techniques used for genetic profiling in disaster victim identification (DVI). The environmental conditions of a mass disaster often result in severe fragmentation, decomposition and intermixing of the remains of victims. In such cases, traditional identification based on the anthropological and physical characteristics of the victims is frequently inconclusive. This is the reason why DNA profiling became the gold standard for victim identification in mass-casualty incidents (MCIs) or any forensic cases where human remains are highly fragmented and/or degraded beyond recognition. The review provides general information about the sources of genetic material for DNA profiling, the genetic markers routinely used during genetic profiling (STR markers, mtDNA and single-nucleotide polymorphisms [SNP]) and the basic statistical approaches used in DNA-based disaster victim identification. Automated technological platforms that allow the simultaneous analysis of a multitude of genetic markers used in genetic identification (oligonucleotide microarray techniques and next-generation sequencing) are also presented. Forensic and population databases containing information on human variability, routinely used for statistical analyses, are discussed. The final part of this review is focused on recent developments, which offer particularly promising tools for forensic applications (mRNA analysis, transcriptome variation in individuals/populations and genetic profiling of specific cells separated from mixtures).

Spectroscopic techniques (Mössbauer spectrometry, NMR, ESR,…) as tools to resolve doubtful NMR images: Study of the craniopharyngioma tumor

NASA Astrophysics Data System (ADS)

Rimbert, J. N.; Dumas, F.; Lafargue, C.; Kellershohn, C.; Brunelle, F.; Lallemand, D.

1990-07-01

Craniopharyngioma, an intracranial tumor, exhibits hyperintensity in the Spin-Echo-T2-NMR image and a hyposignal in the SE-T1-image. However, in some cases (15-20% cases), hypersignals are seen in both SE-T1 and T2-MRI. Using spectroscopic techniques, Mössbauer spectrometry in particular, we have demonstrated that the T1 hypersignal is due to ferritin, dissolved in the cystic liquid, after tumor cell lysis, in the course of time. Other possible reasons inducing a shortening of the T1 relaxation time (presence of lipids, intratumoral hemorrhage) have been rejected.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modeling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-07-01

Ground magnetic anomaly separation using reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prosepecting area in NW Iran. The geophysical survey that resulted in the ground magnetic data was conducted for magnetic elements exploration. Firstly, RTP technique was applied for recognizing underground magnetic anomalies. RTP anomalies was classified to different populations based on this method. For this reason, drilling points determination with RTP technique was complicated. Next, C-A method was applied on the RTP-Magnetic-Anomalies (RTP-MA) for demonstrating magnetic susceptibility concentration. This identification was appropriate for increasing the resolution of the drilling points determination and decreasing the drilling risk, due to the economic costs of underground prospecting. In this study, the results of C-A Modeling on the RTP-MA are compared with 8 borehole data. The results show there is good correlation between anomalies derived via C-A method and log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentration, based on multifractal modeling data analyses, between 63 533.1 and 66 296 nT. Drilling results show appropriate magnetite thickness with the grades greater than 20 % Fe total. Also, anomalies associated with andesite units host iron mineralization.

Spike: Artificial intelligence scheduling for Hubble space telescope

NASA Technical Reports Server (NTRS)

Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

1990-01-01

Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

Toward sensor-based context aware systems.

PubMed

Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo

2012-01-01

This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Global Endometrial Ablation in the Presence of Essure® Microinserts

PubMed Central

Aldape, Diana; Chudnoff, Scott G; Levie, Mark D

2013-01-01

Abnormal uterine bleeding (AUB) affects 30% of women at some time during their reproductive years and is one of the most common reasons a woman sees a gynecologist. Many women are turning to endometrial ablation to manage their AUB. This article reviews the data relating to the available endometrial ablation techniques performed with hysteroscopic sterilization, and focuses on data from patients who had Essure® (Conceptus, San Carlos, CA) coils placed prior to performance of endometrial ablation. Reviewed specifically are data regarding safety and efficacy of these two procedures when combined. Data submitted to the US Food and Drug Administration for the three devices currently approved are reviewed, as well as all published case series. Articles included were selected based on a PubMed search for endometrial ablation (also using the brand names of the different techniques currently available), hysteroscopic sterilization, and Essure. PMID:24358407

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

PubMed

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

Image Processing for Binarization Enhancement via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor)

2009-01-01

A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

A Novel Surgical Technique to Correct Intrareolar Polythelia.

PubMed

Cherubino, Mario; Pellegatta, Igor; Frigo, Claudia; Scamoni, Stefano; Taibi, Dominic; Maggiulli, Francesca; Valdatta, Luigi

2014-07-01

Polythelia is a rare congenital malformation that occurs in 1-2% of the population. Intra-areolar polythelia is the presence of one or more supernumerary nipples located within the areola. This is extremely rare. This article presents 3 cases of intra-areolar polythelia treated at our Department. These cases did not present other associated malformation. Surgical correction was performed for psychological and cosmetic reasons using advancement flaps. The aesthetic and functional results were satisfactory.

The effect of teaching medical ethics on medical students' moral reasoning.

PubMed

Self, D J; Wolinsky, F D; Baldwin, D C

1989-12-01

A study assessed the effect of incorporating medical ethics into the medical curriculum and the relative effects of two methods of implementing that curriculum, namely, lecture and case-study discussions. Results indicate a statistically significant increase (p less than or equal to .0001) in the level of moral reasoning of students exposed to the medical ethics course, regardless of format. Moreover, the unadjusted posttest scores indicated that the case-study method was significantly (p less than or equal to .03) more effective than the lecture method in increasing students' level of moral reasoning. When adjustment were made for the pretest scores, however, this difference was not statistically significant (p less than or equal to .18). Regression analysis by linear panel techniques revealed that age, gender, undergraduate grade-point average, and scores on the Medical College Admission Test were not related to the changes in moral-reasoning scores. All of the variance that could be explained was due to the students' being in one of the two experimental groups. In comparison with the control group, the change associated with each experimental format was statistically significant (lecture, p less than or equal to .004; case study, p less than or equal to .0001). Various explanations for these findings and their implications are given.

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

ERIC Educational Resources Information Center

Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Teaching clinical reasoning: case-based and coached.

PubMed

Kassirer, Jerome P

2010-07-01

Optimal medical care is critically dependent on clinicians' skills to make the right diagnosis and to recommend the most appropriate therapy, and acquiring such reasoning skills is a key requirement at every level of medical education. Teaching clinical reasoning is grounded in several fundamental principles of educational theory. Adult learning theory posits that learning is best accomplished by repeated, deliberate exposure to real cases, that case examples should be selected for their reflection of multiple aspects of clinical reasoning, and that the participation of a coach augments the value of an educational experience. The theory proposes that memory of clinical medicine and clinical reasoning strategies is enhanced when errors in information, judgment, and reasoning are immediately pointed out and discussed. Rather than using cases artificially constructed from memory, real cases are greatly preferred because they often reflect the false leads, the polymorphisms of actual clinical material, and the misleading test results encountered in everyday practice. These concepts foster the teaching and learning of the diagnostic process, the complex trade-offs between the benefits and risks of diagnostic tests and treatments, and cognitive errors in clinical reasoning. The teaching of clinical reasoning need not and should not be delayed until students gain a full understanding of anatomy and pathophysiology. Concepts such as hypothesis generation, pattern recognition, context formulation, diagnostic test interpretation, differential diagnosis, and diagnostic verification provide both the language and the methods of clinical problem solving. Expertise is attainable even though the precise mechanisms of achieving it are not known.

The Special Place Project: Efficacy of a Place-Based Case Study Approach for Teaching Geoscience

NASA Astrophysics Data System (ADS)

Moosavi, Sadredin

2014-05-01

Achieving geoscience literacy of the general population has become increasingly important world wide as ever more connected and growing societies depend more and more on our planet's limited natural resource base. Building citizen understanding of their dependence on the local environment, and the geologic processes which created and continue to change it, has become a great challenge to educators at all levels of the education system. The Special Place Project described in this presentation explores use of a place-based case study approach combining instruction in geoscience content with development of observation, reasoning, writing and presentation skills. The approach allows students to select the locations for their individual case studies affording development of personal connections between the learner and his environment. The approach gives instructors at many grade levels the ability to develop core pedagogical content and skills while exploring the unique geologic environments relevant to the local population including such critical issues as land use, resource depletion, energy, climate change and the future of communities in a changing world. The geologic reasons for the location of communities and key events in their histories can be incorporated into the students' case studies as appropriate. The project is unique in placing all course instruction in the context of the quest to explore and gain understanding of the student's chosen location by using the inherently more generalized course content required by the curriculum. By modeling how scientists approach their research questions, this pedagogical technique not only integrates knowledge and skills from across the curriculum, it captures the excitement of scientific thinking on real world questions directly relevant to students' lives, increasing student engagement and depth of learning as demonstrated in the case study reports crafted by the students and exam results. Student learning of topics directly touched upon by the case study, such as geomorphologic features and processes observable at Earth's surface, is compared to learning on more abstract topics, such as subsurface Earth structure and tectonic processes, to provide a quantitative assessment of this pedagogical approach.

Endoscopic resection of subepithelial tumors

PubMed Central

Schmidt, Arthur; Bauder, Markus; Riecken, Bettina; Caca, Karel

2014-01-01

Management of subepithelial tumors (SETs) remains challenging. Endoscopic ultrasound (EUS) has improved differential diagnosis of these tumors but a definitive diagnosis on EUS findings alone can be achieved in the minority of cases. Complete endoscopic resection may provide a reasonable approach for tissue acquisition and may also be therapeutic in case of malignant lesions. Small SET restricted to the submucosa can be removed with established basic resection techniques. However, resection of SET arising from deeper layers of the gastrointestinal wall requires advanced endoscopic methods and harbours the risk of perforation. Innovative techniques such as submucosal tunneling and full thickness resection have expanded the frontiers of endoscopic therapy in the past years. This review will give an overview about endoscopic resection techniques of SET with a focus on novel methods. PMID:25512768

38 CFR 36.4279 - Extensions and reamortizations.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... (a) Provided the debtor(s) is (are) a reasonable credit risk(s), as determined by the holder based... debtor(s), be extended in the event of default, to avoid imminent default, or in any other case where the...) is (are) a reasonable credit risk(s), as determined by the holder based upon review of the debtor's...

Clinical reasoning of junior doctors in emergency medicine: a grounded theory study.

PubMed

Adams, E; Goyder, C; Heneghan, C; Brand, L; Ajjawi, R

2017-02-01

Emergency medicine (EM) has a high case turnover and acuity making it a demanding clinical reasoning domain especially for junior doctors who lack experience. We aimed to better understand their clinical reasoning using dual cognition as a guiding theory. EM junior doctors were recruited from six hospitals in the south of England to participate in semi-structured interviews (n=20) and focus groups (n=17) based on recall of two recent cases. Transcripts were analysed using a grounded theory approach to identify themes and to develop a model of junior doctors' clinical reasoning in EM. Within cases, clinical reasoning occurred in three phases. In phase 1 (case framing), initial case cues and first impressions were predominantly intuitive, but checked by analytical thought and determined the urgency of clinical assessment. In phase 2 (evolving reasoning), non-analytical single cue and pattern recognitions were common which were subsequently validated by specific analytical strategies such as use of red flags. In phase 3 (ongoing uncertainty) analytical self-monitoring and reassurance strategies were used to precipitate a decision regarding discharge. We found a constant dialectic between intuitive and analytical cognition throughout the reasoning process. Our model of clinical reasoning by EM junior doctors illustrates the specific contextual manifestations of the dual cognition theory. Distinct diagnostic strategies are identified and together these give EM learners and educators a framework and vocabulary for discussion and learning about clinical reasoning. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

1998-01-01

The goal of this project is to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project applies case-based reasoning (CBR) and concept mapping (CMAP) tools to the task of capturing, organizing, and interactively accessing experiences or "cases" encapsulating the methods and rationale underlying expert aerospace design. As stipulated in the award, Indiana University and Ames personnel are collaborating on performance of research and determining the direction of research, to assure that the project focuses on high-value tasks. In the first five months of the project, we have made two visits to Ames Research Center to consult with our NASA collaborators, to learn about the advanced aerospace design tools being developed there, and to identify specific needs for intelligent design support. These meetings identified a number of task areas for applying CBR and concept mapping technology. We jointly selected a first task area to focus on: Acquiring the convergence criteria that experts use to guide the selection of useful data from a set of numerical simulations of high-lift systems. During the first funding period, we developed two software systems. First, we have adapted a CBR system developed at Indiana University into a prototype case-based reasoning shell to capture and retrieve information about design experiences, with the sample task of capturing and reusing experts' intuitive criteria for determining convergence (work conducted at Indiana University). Second, we have also adapted and refined existing concept mapping tools that will be used to clarify and capture the rationale underlying those experiences, to facilitate understanding of the expert's reasoning and guide future reuse of captured information (work conducted at the University of West Florida). The tools we have developed are designed to be the basis for a general framework for facilitating tasks within systems developed by the Advanced Design Technologies Testbed (ADTT) project at ARC. The tenets of our framework are (1) that the systems developed should leverage a designer's knowledge, rather than attempting to replace it; (2) that learning and user feedback must play a central role, so that the system can adapt to how it is used, and (3) that the learning and feedback processes must be as natural and as unobtrusive as possible. In the second funding period we will extend our current work, applying the tools to capturing higher-level design rationale.

Virtual patients design and its effect on clinical reasoning and student experience: a protocol for a randomised factorial multi-centre study.

PubMed

Bateman, James; Allen, Maggie E; Kidd, Jane; Parsons, Nick; Davies, David

2012-08-01

Virtual Patients (VPs) are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent) and structured clinical reasoning feedback (present or absent). This is a multi-centre randomised 2 x 2 factorial design study evaluating two independent variables of VP design, branching (present or absent), and structured clinical reasoning feedback (present or absent).The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded.In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for both primary outcomes. This trial will provide robust evidence to support the effectiveness of different designs of virtual patients, based on student performance and evaluation. The cases and all learning materials will be open access and available on a Creative Commons Attribution-Share-Alike license.

Clinical reasoning in neurology: use of the repertory grid technique to investigate the reasoning of an experienced occupational therapist.

PubMed

Kuipers, Kathy; Grice, James W

2009-08-01

The aim of this paper is to describe the use of a structured interview methodology, the repertory grid technique, for investigating the clinical reasoning of an experienced occupational therapist in the domain of upper limb hypertonia as a result of brain injury. Repertory grid interviews were completed before and after exposure to a protocol designed to guide clinical reasoning and decision-making in relation to upper limb neurological rehabilitation. Data were subjected to both qualitative and quantitative analyses. Qualitative analysis focussed on clinical reasoning content. Common themes across the pre- and post-exposure interviews were the use of theoretical frameworks and practice models, the significance of clinical expertise, and discrimination of 'broad' and 'specific' aspects, as well as differentiation between 'therapist and client-related' aspects of the clinical situation. Quantitative analysis indicated that for both pre- and post-exposure repertory grids, clinical reasoning was structured in terms of two main concepts. In the pre-exposure grid, these were related to the therapist's role, and to the 'scope' of practice tasks (either broad or specific). In the post-exposure grid the two main concepts were upper limb performance, and client-centred aspects of the therapy process. The repertory grid technique is proposed as an effective tool for exploring occupational therapy clinical reasoning, based on its capacity for accessing personal frames of reference, and elucidating both the meaning and the structure supporting clinical reasoning.

Comprehensive Analysis of Semantic Web Reasoners and Tools: A Survey

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Technology-based strategies for promoting clinical reasoning skills in nursing education.

PubMed

Shellenbarger, Teresa; Robb, Meigan

2015-01-01

Faculty face the demand of preparing nursing students for the constantly changing health care environment. Effective use of online, classroom, and clinical conferencing opportunities helps to enhance nursing students' clinical reasoning capabilities needed for practice. The growth of technology creates an avenue for faculty to develop engaging learning opportunities. This article presents technology-based strategies such as electronic concept mapping, electronic case histories, and digital storytelling that can be used to facilitate clinical reasoning skills.

Emotional reasoning and parent-based reasoning in normal children.

PubMed

Morren, Mattijn; Muris, Peter; Kindt, Merel

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their own anxiety-response. The present study further examined emotional reasoning in children aged 7-13 years (N = 508). In addition, it was investigated whether children also show parent-based reasoning, which can be defined as the tendency to rely on anxiety-responses that can be observed in parents. Children completed self-report questionnaires of anxiety, depression, and emotional and parent-based reasoning. Evidence was found for both emotional and parent-based reasoning effects. More specifically, children's danger ratings were not only affected by objective danger information, but also by anxiety-response information in both objective danger and safety stories. High levels of anxiety and depression were significantly associated with the tendency to rely on anxiety-response information, but only in the case of safety scripts.

Comparison of ethical judgments exhibited by clients and ethics consultants in Japan

PubMed Central

2014-01-01

Background Healthcare professionals must make decisions for patients based on ethical considerations. However, they rely on clinical ethics consultations (CEC) to review ethical justifications of their decisions. CEC consultants support the cases reviewed and guide medical care. When both healthcare professionals and CEC consultants face ethical problems in medical care, how is their judgment derived? How do medical judgments differ from the ethical considerations of CECs? This study examines CECs in Japan to identify differences in the ethical judgment of clients and CEC consultants. Methods The CEC request and response documents of all 60 cases reviewed across Japan between October 2006 and the end of October 2011 were classified in terms of the presence of decisional capacity in the patient. We conducted a qualitative content analysis of the differences in reasoning between client and CEC consultants. Reasoned judgments were verified in individual cases to classify the similarities or differences of opinion between CEC clients and teams. Results As the result of classification of the decisional capacity and the difference of opinion regarding medical care, the most frequent category was 25 cases (41.7%) of “uncertain decisional capacity,” and 23 cases (38.3%) of “withholding of decision-making.” A chi-square analysis was performed on presence of decisional capacity and agreement in decision-making, yielding a statistically significant difference (p < 0.05). The CEC consultants’ reasoning was based on “patient’s preference was ambiguous,” “validity of family as a surrogate,” “estimation of patient preference,” and “patient’s best interest,” whereas the CEC client’s reasoning was based on “consistent family preference was shown/not shown” and “appropriate therapeutic methods to manage patient safety.” Conclusion Differences in opinions were found in cases classified according to decisional capacity. Furthermore, the reasoning behind judgments differed between CEC clients and CEC consultants. The reasoning of CEC consultants was critical and reflective, while for clients it was situational and pragmatic. PMID:24592932

Case based reasoning in criminal intelligence using forensic case data.

PubMed

Ribaux, O; Margot, P

2003-01-01

A model that is based on the knowledge of experienced investigators in the analysis of serial crime is suggested to bridge a gap between technology and methodology. Its purpose is to provide a solid methodology for the analysis of serial crimes that supports decision making in the deployment of resources, either by guiding proactive policing operations or helping the investigative process. Formalisation has helped to derive a computerised system that efficiently supports the reasoning processes in the analysis of serial crime. This novel approach fully integrates forensic science data.

A Research Project-Based and Self-Determined Teaching System of Molecular Biology Techniques for Undergraduates

ERIC Educational Resources Information Center

Zhang, Shuping

2008-01-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a…

MTK: An AI tool for model-based reasoning

NASA Technical Reports Server (NTRS)

Erickson, William K.; Rudokas, Mary R.

1988-01-01

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Office is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control, and trend analysis of the Space Station Thermal Control System (TCS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined here with examples from the thermal system to highlight the motivating factors behind them, followed by an overview of the capabilities of MTK, which was developed to address these issues in a generic fashion.

Case-Based Plan Recognition Using Action Sequence Graphs

DTIC Science & Technology

2014-10-01

resized as necessary. Similarly, trace- based reasoning (Zarka et al., 2013) and episode -based reasoning (Sánchez-Marré, 2005) store fixed-length...is a goal state of Π, where satisfies has the same semantics as originally laid out in Ghallab, Nau & Traverso (2004). Action 0 is ...Although there are syntactic similarities between planning encoding graphs and action sequence graphs, important semantic differences exist because the

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

Self-harming behavior of a parent with borderline personality disorder assessed using revealed preference and attributional approaches: a case study.

PubMed

Tustin, R Don

2002-08-01

This article discusses a case study involving a parent with Borderline Personality Disorder who exhibited self-harming behaviors. Assessment and intervention were based both on a review of the client's attributions about causes of her own behavior as being either internalizing or externalizing, and on a review of motivation of the behaviors using functional analysis. Antecedent situations for self-harming behaviors were identified to provide a basis for reviewing the client's attributions of reasons for disordered behavior. A new technique of functional analysis was applied using the principle of revealed preference arising from behavioral economics. Revealed preference identified outcomes that were valued by the client, enabling new responses to be identified to attain these reinforcers. Attribution re-training was provided. Significant reductions in self-harming behaviors were achieved during brief therapy and were maintained during follow-up.

Rhinoplasty: The Asymmetric Crooked Nose-An Overview.

PubMed

Kosins, Aaron M; Daniel, Rollin K; Nguyen, Dananh P

2016-08-01

There are three reasons why the asymmetric crooked nose is one of the greatest challenges in rhinoplasty surgery. First, the complexity of the problem is not appreciated by the patient nor understood by the surgeon. Patients often see the obvious deviation of the nose, but not the distinct differences between the right and left sides. Surgeons fail to understand and to emphasize to the patient that each component of the nose is asymmetric. Second, these deformities can be improved, but rarely made flawless. For this reason, patients are told that the result will be all "-er words," better, straighter, cuter, but no "t-words," there is no perfect nor straight. Most surgeons fail to realize that these cases represent asymmetric noses on asymmetric faces with the variable of ipsilateral and contralateral deviations. Third, these cases demand a wide range of sophisticated surgical techniques, some of which have a minimal margin of error. This article offers an in-depth look at analysis, preoperative planning, and surgical techniques available for dealing with the asymmetric crooked nose. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

A Novel Surgical Technique to Correct Intrareolar Polythelia

PubMed Central

Cherubino, Mario; Pellegatta, Igor; Frigo, Claudia; Scamoni, Stefano; Taibi, Dominic; Maggiulli, Francesca; Valdatta, Luigi

2014-01-01

Polythelia is a rare congenital malformation that occurs in 1–2% of the population. Intra-areolar polythelia is the presence of one or more supernumerary nipples located within the areola. This is extremely rare. This article presents 3 cases of intra-areolar polythelia treated at our Department. These cases did not present other associated malformation. Surgical correction was performed for psychological and cosmetic reasons using advancement flaps. The aesthetic and functional results were satisfactory. PMID:28331667

Advanced digital modulation: Communication techniques and monolithic GaAs technology

NASA Technical Reports Server (NTRS)

Wilson, S. G.; Oliver, J. D., Jr.; Kot, R. C.; Richards, C. R.

1983-01-01

Communications theory and practice are merged with state-of-the-art technology in IC fabrication, especially monolithic GaAs technology, to examine the general feasibility of a number of advanced technology digital transmission systems. Satellite-channel models with (1) superior throughput, perhaps 2 Gbps; (2) attractive weight and cost; and (3) high RF power and spectrum efficiency are discussed. Transmission techniques possessing reasonably simple architectures capable of monolithic fabrication at high speeds were surveyed. This included a review of amplitude/phase shift keying (APSK) techniques and the continuous-phase-modulation (CPM) methods, of which MSK represents the simplest case.

An ontological case base engineering methodology for diabetes management.

PubMed

El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

2014-08-01

Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

[Technical considerations on 222 cases of esophageal anastomosis using a stapler].

PubMed

Liboni, A; Zamboni, P; Mari, C; Uzzau, A; Salomoni, C; Brunelli, G; Buccoliero, F; Donini, I

1989-05-01

The Authors report their experience with 222 esophagoenteric anastomoses, performed in 211 cases for malignant neoplasms (middle and lower third) of the esophagus or stomach. Particularly, they have performed 4 Sujura operations, 31 esophagogastric, 4 esophagocolic, 183 esophagojejunal anastomoses utilizing SPTU, ILS and EEA circular stapler. GIA was used in the preparation of the stomach before esophagogastroplasty. Mortality rate of the manual period (1970-1980: 114 cases operated) was 14.5% versus 2.2% of the stapling period (1981-1987: 222 cases operated). From the technical point of view reasons of the superiority of stapled technique are discussed and summarized as follows: 1) space not favourable for handsewn anastomoses; 2) stapled technique allows the surgeon to save anastomoses vascularization; 3) the stapler performs the suture simultaneously so to reduce tensile strength on the anastomoses and the fragile esophageal wall especially; 4) stapled agraphes are fixed in three points vs. the two points of the handsewn stitches.

Lifting the veil: a typological survey of the methodological features of Islamic ethical reasoning on biomedical issues.

PubMed

Abdur-Rashid, Khalil; Furber, Steven Woodward; Abdul-Basser, Taha

2013-04-01

We survey the meta-ethical tools and institutional processes that traditional Islamic ethicists apply when deliberating on bioethical issues. We present a typology of these methodological elements, giving particular attention to the meta-ethical techniques and devices that traditional Islamic ethicists employ in the absence of decisive or univocal authoritative texts or in the absence of established transmitted cases. In describing how traditional Islamic ethicists work, we demonstrate that these experts possess a variety of discursive tools. We find that the ethical responsa-i.e., the products of the application of the tools that we describe-are generally characterized by internal consistency. We also conclude that Islamic ethical reasoning on bioethical issues, while clearly scripture-based, is also characterized by strong consequentialist elements and possesses clear principles-based characteristics. The paper contributes to the study of bioethics by familiarizing non-specialists in Islamic ethics with the role, scope, and applicability of key Islamic ethical concepts, such as "aims" (maqāṣid), "universals" (kulliyyāt), "interest" (maṣlaḥa), "maxims" (qawā`id), "controls" (ḍawābit), "differentiators" (furūq), "preponderization" (tarjīḥ), and "extension" (tafrī`).

LinguisticBelief: a java application for linguistic evaluation using belief, fuzzy sets, and approximate reasoning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Darby, John L.

LinguisticBelief is a Java computer code that evaluates combinations of linguistic variables using an approximate reasoning rule base. Each variable is comprised of fuzzy sets, and a rule base describes the reasoning on combinations of variables fuzzy sets. Uncertainty is considered and propagated through the rule base using the belief/plausibility measure. The mathematics of fuzzy sets, approximate reasoning, and belief/ plausibility are complex. Without an automated tool, this complexity precludes their application to all but the simplest of problems. LinguisticBelief automates the use of these techniques, allowing complex problems to be evaluated easily. LinguisticBelief can be used free of chargemore » on any Windows XP machine. This report documents the use and structure of the LinguisticBelief code, and the deployment package for installation client machines.« less

Application of plausible reasoning to AI-based control systems

NASA Technical Reports Server (NTRS)

Berenji, Hamid; Lum, Henry, Jr.

1987-01-01

Some current approaches to plausible reasoning in artificial intelligence are reviewed and discussed. Some of the most significant recent advances in plausible and approximate reasoning are examined. A synergism among the techniques of uncertainty management is advocated, and brief discussions on the certainty factor approach, probabilistic approach, Dempster-Shafer theory of evidence, possibility theory, linguistic variables, and fuzzy control are presented. Some extensions to these methods are described, and the applications of the methods are considered.

Estimating Am-241 activity in the body: comparison of direct measurements and radiochemical analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lynch, Timothy P.; Tolmachev, Sergei Y.; James, Anthony C.

2009-06-01

The assessment of dose and ultimately the health risk from intakes of radioactive materials begins with estimating the amount actually taken into the body. An accurate estimate provides the basis to best assess the distribution in the body, the resulting dose, and ultimately the health risk. This study continues the time-honored practice of evaluating the accuracy of results obtained using in vivo measurement methods and techniques. Results from the radiochemical analyses of the 241Am activity content of tissues and organs from four donors to the United States Transuranium and Uranium Registries were compared to the results from direct measurements ofmore » radioactive material in the body performed in vivo and post mortem. Two were whole body donations and two were partial body donations The skeleton was the organ with the highest deposition of 241Am activity in all four cases. The activities ranged from 30 Bq to 300 Bq. The skeletal estimates obtained from measurements over the forehead were within 20% of the radiochemistry results in three cases and differed by 78% in one case. The 241Am lung activity estimates ranged from 1 Bq to 30 Bq in the four cases. The results from the direct measurements were within 40% of the radiochemistry results in 3 cases and within a factor of 3 for the other case. The direct measurement estimates of liver activity ranged from 2 Bq to 60 Bq and were generally lower than the radiochemistry results. The results from this study suggest that the measurement methods and calibration techniques used at the In Vivo Radiobioassay and Research Facility to quantify the activity in the lungs, skeleton and liver are reasonable under the most challenging conditions where there is 241Am activity in multiple organs. These methods and techniques are comparable to those used at other Department of Energy sites. This suggests that the current in vivo methods and calibration techniques provide reasonable estimates of radioactive material in the body. Not unexpectedly, there can be significant uncertainty in the estimates especially when activity is also present in other organs.« less

Reasonable Accommodation Information Tracking System

EPA Pesticide Factsheets

The Reasonable Accommodation Information Tracking System (RAITS) is a case management system that allows the National Reasonable Accommodation Coordinator (NRAC) and the Local Reasonable Accommodation Coordinators (LORAC) to manage information related to Reasonable Accommodation (RA) requests. It provides a data base system in compliance with Executive Order 13164 and required by the Equal Employment Opportunity Commission (EEOC) Regulations and American Federation of Government Employees (AFGE) Bargaining Unit as described in the AFGE National Reasonable Accommodation Procedures. It is a tool that was internally developed in Lotus Notes to track requests for reasonable accommodation and was custom-configured to meet EPA's specific needs and infrastructure.

Real-time passenger counting by active linear cameras

NASA Astrophysics Data System (ADS)

Khoudour, Louahdi; Duvieubourg, Luc; Deparis, Jean-Pierre

1996-03-01

The companies operating subways are very much concerned with counting the passengers traveling through their transport systems. One of the most widely used systems for counting passengers consists of a mechanical gate equipped with a counter. However, such simple systems are not able to count passengers jumping above the gates. Moreover, passengers carrying large luggage or bags may meet some difficulties when going through such gates. The ideal solution is a contact-free counting system that would bring more comfort of use for the passengers. For these reasons, we propose to use a video processing system instead of these mechanical gates. The optical sensors discussed in this paper offer several advantages including well defined detection areas, fast response time and reliable counting capability. A new technology has been developed and tested, based on linear cameras. Preliminary results show that this system is very efficient when the passengers crossing the optical gate are well separated. In other cases, such as in compact crowd conditions, reasonable accuracy has been demonstrated. These results are illustrated by means of a number of sequences shot in field conditions. It is our belief that more precise measurements could be achieved, in the case of compact crowd, by other algorithms and acquisition techniques of the line images that we are presently developing.

Does Medical Students' Diagnostic Performance Improve by Observing Examples of Self-Explanation Provided by Peers or Experts?

ERIC Educational Resources Information Center

Chamberland, Martine; Mamede, Sílvia; St-Onge, Christina; Setrakian, Jean; Schmidt, Henk G.

2015-01-01

Educational strategies that promote the development of clinical reasoning in students remain scarce. Generating self-explanations (SE) engages students in active learning and has shown to be an effective technique to improve clinical reasoning in clerks. Example-based learning has been shown to support the development of accurate knowledge…

Risk assessment and optimization (ALARA) analysis for the environmental remediation of Brookhaven National Laboratory`s hazardous waste management facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dionne, B.J.; Morris, S.C. III; Baum, J.W.

1998-01-01

The Department of Energy`s (DOE) Office of Environment, Safety, and Health (EH) sought examples of risk-based approaches to environmental restoration to include in their guidance for DOE nuclear facilities. Extensive measurements of radiological contamination in soil and ground water have been made at Brookhaven National Laboratory`s Hazardous Waste Management Facility (HWMF) as part of a Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) remediation process. This provided an ideal opportunity for a case study. This report provides a risk assessment and an {open_quotes}As Low as Reasonably Achievable{close_quotes} (ALARA) analysis for use at other DOE nuclear facilities as an example ofmore » a risk-based decision technique. This document contains the Appendices for the report.« less

Implementation of a Clinical Reasoning Course in the Internal Medicine trimester of the final year of undergraduate medical training and its effect on students' case presentation and differential diagnostic skills.

PubMed

Harendza, Sigrid; Krenz, Ingo; Klinge, Andreas; Wendt, Ulrike; Janneck, Matthias

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in "Summarizing and presentation of a paper case" or in the "Skill to enumerate differential diagnoses" (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students' self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible.

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study.

PubMed

Chandrasekar, Hamsika; Gesundheit, Neil; Nevins, Andrew B; Pompei, Peter; Bruce, Janine; Merrell, Sylvia Bereknyei

2018-01-01

It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student-faculty interaction. Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student-faculty interaction and the use of visual aids ( P < 0.05). The results of our feasibility study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student-faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the development of clinical reasoning skills.

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study

PubMed Central

Chandrasekar, Hamsika; Gesundheit, Neil; Nevins, Andrew B; Pompei, Peter; Bruce, Janine; Merrell, Sylvia Bereknyei

2018-01-01

Background It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student–faculty interaction. Methods Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Results Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student–faculty interaction and the use of visual aids (P < 0.05). Conclusion The results of our feasibility study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student–faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the development of clinical reasoning skills. PMID:29692641

Toxic release consequence analysis tool (TORCAT) for inherently safer design plant.

PubMed

Shariff, Azmi Mohd; Zaini, Dzulkarnain

2010-10-15

Many major accidents due to toxic release in the past have caused many fatalities such as the tragedy of MIC release in Bhopal, India (1984). One of the approaches is to use inherently safer design technique that utilizes inherent safety principle to eliminate or minimize accidents rather than to control the hazard. This technique is best implemented in preliminary design stage where the consequence of toxic release can be evaluated and necessary design improvements can be implemented to eliminate or minimize the accidents to as low as reasonably practicable (ALARP) without resorting to costly protective system. However, currently there is no commercial tool available that has such capability. This paper reports on the preliminary findings on the development of a prototype tool for consequence analysis and design improvement via inherent safety principle by utilizing an integrated process design simulator with toxic release consequence analysis model. The consequence analysis based on the worst-case scenarios during process flowsheeting stage were conducted as case studies. The preliminary finding shows that toxic release consequences analysis tool (TORCAT) has capability to eliminate or minimize the potential toxic release accidents by adopting the inherent safety principle early in preliminary design stage. 2010 Elsevier B.V. All rights reserved.

Case-based clinical reasoning in feline medicine: 1: Intuitive and analytical systems.

PubMed

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-01-01

This is Article 1 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. This first article discusses the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). Articles 2 and 3, to appear in the March and May 2016 issues of JFMS, respectively, will examine managing cognitive error, and use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Comparison of the sensitivity of mass spectrometry atmospheric pressure ionization techniques in the analysis of porphyrinoids.

PubMed

Swider, Paweł; Lewtak, Jan P; Gryko, Daniel T; Danikiewicz, Witold

2013-10-01

The porphyrinoids chemistry is greatly dependent on the data obtained in mass spectrometry. For this reason, it is essential to determine the range of applicability of mass spectrometry ionization methods. In this study, the sensitivity of three different atmospheric pressure ionization techniques, electrospray ionization, atmospheric pressure chemical ionization and atmospheric pressure photoionization, was tested for several porphyrinods and their metallocomplexes. Electrospray ionization method was shown to be the best ionization technique because of its high sensitivity for derivatives of cyanocobalamin, free-base corroles and porphyrins. In the case of metallocorroles and metalloporphyrins, atmospheric pressure photoionization with dopant proved to be the most sensitive ionization method. It was also shown that for relatively acidic compounds, particularly for corroles, the negative ion mode provides better sensitivity than the positive ion mode. The results supply a lot of relevant information on the methodology of porphyrinoids analysis carried out by mass spectrometry. The information can be useful in designing future MS or liquid chromatography-MS experiments. Copyright © 2013 John Wiley & Sons, Ltd.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

NASA Astrophysics Data System (ADS)

Adnan, Arisman; Sugiarto, Sigit

2017-06-01

The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

"For Some Reason, I'm Just Tired": Women Domestic Workers Persisting in Community-Based Programmes

ERIC Educational Resources Information Center

Cuban, Sondra

2007-01-01

A study of women migrant domestic workers in the USA and their reasons for participating and persisting in community-based literacy and ESOL programmes is presented. Case studies and themes were developed about the women's experiences of work life and how it connected to their programme participation. The findings revealed that the women had…

Septorhinoplasty: Our Experience.

PubMed

Bakshi, Jaimanti; Patro, Sourabha K

2017-09-01

Rhinoplasty is one of the oldest known surgeries to the human kind. However, being a cosmetic of surgery of utmost importance, it has been an attractive and fascinating surgery for the otolaryngologists and plastic surgeons. Along with the evolution of improved techniques and better surgical modalities, this surgery has been growing in panorama including its indications, needs and techniques. We present our experience with rhinoplasty in a tertiary care center of north India. We have included all cases operated with septorhinoplasty from 2001 to 2014 by the senior author in the manuscript. We reviewed their presentations, investigations, preoperative counselling records, operative details and post-operative clinical records to audit our results and hence to document our experiences in septorhinoplasties. A total of 53 cases including 37 males and 16 females had undergone rhinoplasty surgeries. The most common reason of disfigurement was road traffic accident (58.5%). All these patients included different deformities and required varied corrections. There were no major post-operative complications except persistent edema with longest lasting for 23 weeks. Thermal splints gave a better patient satisfaction in post-op compared to POP splints. Results were completely and partially satisfying for 50 patients and not satisfying for three. Unrealistic expectations from the procedure might be the reason for non-satisfactory results in rhinoplasty. Rhinoplasty is a delicate procedure and has greater aesthetic implications in planning surgical techniques and approaches. For better satisfaction of patients, adequate preoperative counseling and realistic expectations are warranted. Skillful surgical techniques null chances of complications.

Evaluating reasons for nursing turnover: comparison of exit interview and panel data.

PubMed

Weisman, C S; Alexander, C S; Chase, G A

1981-06-01

Data from a study of nursing turnover are used to compare findings based on two techniques for evaluating the reasons for resignations within the same population of hospital nurses during one year. The techniques are: (1) exit interviews, in which resigning nurses were asked to report in an open-ended format their major reasons for leaving their jobs; and (2) a prospective panel study, in which nurses who resigned are compared with nurses who remained, and actual turnover is predicted. Results show that due to the absence of a comparison group of remaining nurses and of baseline data, causal inferences based on exit interview data alone are overly simplistic and misleading for management purposes. Results of the panel study are more informative, although implications for hospital management are more complex. Use of the prospective panel design is recommended for hospitals concerned with evaluating nursing job conditions during a period of high turnover and staff nurse shortages.

Applying temporal abstraction and case-based reasoning to predict approaching influenza waves.

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

The goal of the TeCoMed project is to send early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, to interested practitioners, pharmacists etc. in the German federal state Mecklenburg-Western Pomerania. The forecast of these waves is based on written confirmations of unfitness for work of the main German health insurance company. Since influenza waves are difficult to predict because of their cyclic but not regular behaviour, statistical methods based on the computation of mean values are not helpful. Instead, we have developed a prognostic model that makes use of similar former courses. Our method combines Case-based Reasoning with Temporal Abstraction to decide whether early warning is appropriate.

Approximation methods for stochastic petri nets

NASA Technical Reports Server (NTRS)

Jungnitz, Hauke Joerg

1992-01-01

Stochastic Marked Graphs are a concurrent decision free formalism provided with a powerful synchronization mechanism generalizing conventional Fork Join Queueing Networks. In some particular cases the analysis of the throughput can be done analytically. Otherwise the analysis suffers from the classical state explosion problem. Embedded in the divide and conquer paradigm, approximation techniques are introduced for the analysis of stochastic marked graphs and Macroplace/Macrotransition-nets (MPMT-nets), a new subclass introduced herein. MPMT-nets are a subclass of Petri nets that allow limited choice, concurrency and sharing of resources. The modeling power of MPMT is much larger than that of marked graphs, e.g., MPMT-nets can model manufacturing flow lines with unreliable machines and dataflow graphs where choice and synchronization occur. The basic idea leads to the notion of a cut to split the original net system into two subnets. The cuts lead to two aggregated net systems where one of the subnets is reduced to a single transition. A further reduction leads to a basic skeleton. The generalization of the idea leads to multiple cuts, where single cuts can be applied recursively leading to a hierarchical decomposition. Based on the decomposition, a response time approximation technique for the performance analysis is introduced. Also, delay equivalence, which has previously been introduced in the context of marked graphs by Woodside et al., Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's is slower, but the accuracy is generally better. Delay equivalence often fails to converge, while flow equivalent aggregation can lead to potentially bad results if a strong dependence of the mean completion time on the interarrival process exists.

Scientific reasoning profile of junior secondary school students on the concept of static fluid

NASA Astrophysics Data System (ADS)

Mariana, N.; Siahaan, P.; Utari, S.

2018-05-01

Scientific reasoning is one of the most important ability. This study aims to determine the profile of scientific reasoning of junior high school students about the concept of static fluid. This research uses a descriptive method with a quantitative approach to get an idea about the scientific reasoning of One Roof Junior Secondary School Student Kotabaru Reteh in Riau. The technique of collecting data is done by test of scientific reasoning. Scientific reasoning capability refers to Furtak’s EBR (Evidence Based Reasoning) scientific reasoning indicator that contains the components of claims, data, evidence, and rules. The result obtained on each element of scientific reasoning is 35% claim, 23% data, 21% evidence and 17% rule. The conclusions of this research that scientific reasoning of Satu Atap Junior Secondary School student Kotabaru Reteh, Riau Province still in the low category.

Development of critical attitude in fundamentals of professional care discipline: a case study.

PubMed

Waterkemper, Roberta; do Prado, Marta Lenise; Medina, Jose Luis Moya; Reibnitz, Kenya Schmidt

2014-04-01

This is a qualitative case study to identify the contributions of a critical pedagogical technique in developing critical attitudes of graduating nursing students in Brazil. Fourteen students participated in this study. Data were collected from March to August 2010 using triangulation of non-participant observation, interview and document analysis. The collected data were transcribed to Word documents, which were subsequently imported into ATLAS.ti, version 6.2, for organisation and qualitative data analysis. The analysis was based on the work of Minayo (2010). The following three thematic analysis units were constructed: feeling free - seeking the liberty to learn to admire, admiring by curiosity and reflecting about the admired object. The results of the thematic categories reveal that the students understand that they are free to have an active role in their education, and the teacher facilitates this process; thus, the students have a raison d'ètre, or reason for being, free. Feeling free, the student can exercise their curiosity when facing the given situations and topics, which challenges them to make decisions based on their awareness of the world. © 2013.

Assessing the use of cognitive heuristic representativeness in clinical reasoning.

PubMed

Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca

2008-11-06

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

PubMed Central

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140

Evaluating moral reasoning in nursing education.

PubMed

McLeod-Sordjan, Renee

2014-06-01

Evidence-based practice suggests the best approach to improving professionalism in practice is ethics curricula. However, recent research has demonstrated that millennium graduates do not advocate for patients or assert themselves during moral conflicts. The aim of this article is the exploration of evaluation techniques to evaluate one measurable outcome of ethics curricula: moral reasoning. A review of literature, published between 1995 and 2013, demonstrated that the moral orientations of care and justice as conceptualized by Gilligan and Kohlberg are utilized by nursing students to solve ethical dilemmas. Data obtained by means of reflective journaling, Ethics of Care Interview (ECI) and Defining Issues Test (DIT), would objectively measure the interrelated pathways of care-based and justice-based moral reasoning. In conclusion, educators have an ethical responsibility to foster students' ability to exercise sound clinical judgment, and support their professional development. It is recommended that educators design authentic assessments to demonstrate student's improvement of moral reasoning. © The Author(s) 2013.

Design of a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oriented clustering case-based reasoning mechanism.

PubMed

Ku, Hao-Hsiang

2015-01-01

Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers.

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

An Intelligent Case-Based Help Desk Providing Web-Based Support for EOSDIS Customers

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.; Thurman, David A.

1998-01-01

This paper describes a project that extends the concept of help desk automation by offering World Wide Web access to a case-based help desk. It explores the use of case-based reasoning and cognitive engineering models to create an 'intelligent' help desk system, one that learns. It discusses the AutoHelp architecture for such a help desk and summarizes the technologies used to create a help desk for NASA data users.

Load Balancing in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Zhu, Yingwu

In this chapter we start by addressing the importance and necessity of load balancing in structured P2P networks, due to three main reasons. First, structured P2P networks assume uniform peer capacities while peer capacities are heterogeneous in deployed P2P networks. Second, resorting to pseudo-uniformity of the hash function used to generate node IDs and data item keys leads to imbalanced overlay address space and item distribution. Lastly, placement of data items cannot be randomized in some applications (e.g., range searching). We then present an overview of load aggregation and dissemination techniques that are required by many load balancing algorithms. Two techniques are discussed including tree structure-based approach and gossip-based approach. They make different tradeoffs between estimate/aggregate accuracy and failure resilience. To address the issue of load imbalance, three main solutions are described: virtual server-based approach, power of two choices, and address-space and item balancing. While different in their designs, they all aim to improve balance on the address space and data item distribution. As a case study, the chapter discusses a virtual server-based load balancing algorithm that strives to ensure fair load distribution among nodes and minimize load balancing cost in bandwidth. Finally, the chapter concludes with future research and a summary.

Comprehension and retrieval of failure cases in airborne observatories

NASA Technical Reports Server (NTRS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-01-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Comprehension and retrieval of failure cases in airborne observatories

NASA Astrophysics Data System (ADS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-05-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases

NASA Astrophysics Data System (ADS)

Pinzón, Cristian; de Paz, Yanira; Bajo, Javier; Abraham, Ajith; Corchado, Juan M.

One of the main attacks to ubiquitous databases is the structure query language (SQL) injection attack, which causes severe damages both in the commercial aspect and in the user’s confidence. This chapter proposes the SiC architecture as a solution to the SQL injection attack problem. This is a hierarchical distributed multiagent architecture, which involves an entirely new approach with respect to existing architectures for the prevention and detection of SQL injections. SiC incorporates a kind of intelligent agent, which integrates a case-based reasoning system. This agent, which is the core of the architecture, allows the application of detection techniques based on anomalies as well as those based on patterns, providing a great degree of autonomy, flexibility, robustness and dynamic scalability. The characteristics of the multiagent system allow an architecture to detect attacks from different types of devices, regardless of the physical location. The architecture has been tested on a medical database, guaranteeing safe access from various devices such as PDAs and notebook computers.

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Selecting a software development methodology. [of digital flight control systems

NASA Technical Reports Server (NTRS)

Jones, R. E.

1981-01-01

The state of the art analytical techniques for the development and verification of digital flight control software is studied and a practical designer oriented development and verification methodology is produced. The effectiveness of the analytic techniques chosen for the development and verification methodology are assessed both technically and financially. Technical assessments analyze the error preventing and detecting capabilities of the chosen technique in all of the pertinent software development phases. Financial assessments describe the cost impact of using the techniques, specifically, the cost of implementing and applying the techniques as well as the relizable cost savings. Both the technical and financial assessment are quantitative where possible. In the case of techniques which cannot be quantitatively assessed, qualitative judgements are expressed about the effectiveness and cost of the techniques. The reasons why quantitative assessments are not possible will be documented.

Validity and reliability of an instrument for assessing case analyses in bioengineering ethics education.

PubMed

Goldin, Ilya M; Pinkus, Rosa Lynn; Ashley, Kevin

2015-06-01

Assessment in ethics education faces a challenge. From the perspectives of teachers, students, and third-party evaluators like the Accreditation Board for Engineering and Technology and the National Institutes of Health, assessment of student performance is essential. Because of the complexity of ethical case analysis, however, it is difficult to formulate assessment criteria, and to recognize when students fulfill them. Improvement in students' moral reasoning skills can serve as the focus of assessment. In previous work, Rosa Lynn Pinkus and Claire Gloeckner developed a novel instrument for assessing moral reasoning skills in bioengineering ethics. In this paper, we compare that approach to existing assessment techniques, and evaluate its validity and reliability. We find that it is sensitive to knowledge gain and that independent coders agree on how to apply it.

Colovesical fistula causing an uncommon reason for failure of computed tomography colonography: a case report.

PubMed

Neroladaki, Angeliki; Breguet, Romain; Botsikas, Diomidis; Terraz, Sylvain; Becker, Christoph D; Montet, Xavier

2012-07-23

Computed tomography colonography, or virtual colonoscopy, is a good alternative to optical colonoscopy. However, suboptimal patient preparation or colon distension may reduce the diagnostic accuracy of this imaging technique. We report the case of an 83-year-old Caucasian woman who presented with a five-month history of pneumaturia and fecaluria and an acute episode of macrohematuria, leading to a high clinical suspicion of a colovesical fistula. The fistula was confirmed by standard contrast-enhanced computed tomography. Optical colonoscopy was performed to exclude the presence of an underlying colonic neoplasm. Since optical colonoscopy was incomplete, computed tomography colonography was performed, but also failed due to inadequate colon distension. The insufflated air directly accumulated within the bladder via the large fistula. Clinicians should consider colovesical fistula as a potential reason for computed tomography colonography failure.

Implementation of a Clinical Reasoning Course in the Internal Medicine trimester of the final year of undergraduate medical training and its effect on students' case presentation and differential diagnostic skills

PubMed Central

Harendza, Sigrid; Krenz, Ingo; Klinge, Andreas; Wendt, Ulrike; Janneck, Matthias

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in “Summarizing and presentation of a paper case” or in the “Skill to enumerate differential diagnoses” (p<0.05). The greatest increase occurred in the skill to recognize typical cognitive errors in medicine and to identify risk situations for their occurrence (pre: 2.98±0.92 and retro-pre: 2.64±1.01, respectively, versus post: 4.38±0.88). Based on the ratio of number of words used per keywords used the problem presentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students’ self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical curriculum seems to be desirable. Faculty training would be useful to implement the concept as standardized as possible. PMID:29226234

Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator.

PubMed

Nguyen, Sy Dzung; Vo, Hoang Duy; Seo, Tae-Il

2017-09-01

It is difficult to efficiently control nonlinear systems in the presence of uncertainty and disturbance (UAD). One of the main reasons derives from the negative impact of the unknown features of UAD as well as the response delay of the control system on the accuracy rate in the real time of the control signal. In order to deal with this, we propose a new controller named CO-FSMC for a class of nonlinear control systems subjected to UAD, which is constituted of a fuzzy sliding mode controller (FSMC) and a fuzzy-based compensator (CO). Firstly, the FSMC and CO are designed independently, and then an adaptive fuzzy structure is discovered to combine them. Solutions for avoiding the singular cases of the fuzzy-based function approximation and reducing the calculating cost are proposed. Based on the solutions, fuzzy sliding mode technique, lumped disturbance observer and Lyapunov stability analysis, a closed-loop adaptive control law is formulated. Simulations along with a real application based on a semi-active train-car suspension are performed to fully evaluate the method. The obtained results reflected that vibration of the chassis mass is insensitive to UAD. Compared with the other fuzzy sliding mode control strategies, the CO-FSMC can provide the best control ability to reduce unwanted vibrations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Evidence in clinical reasoning: a computational linguistics analysis of 789,712 medical case summaries 1983-2012.

PubMed

Seidel, Bastian M; Campbell, Steven; Bell, Erica

2015-03-21

Better understanding of clinical reasoning could reduce diagnostic error linked to 8% of adverse medical events and 30% of malpractice cases. To a greater extent than the evidence-based movement, the clinical reasoning literature asserts the importance of practitioner intuition—unconscious elements of diagnostic reasoning. The study aimed to analyse the content of case report summaries in ways that explored the importance of an evidence concept, not only in relation to research literature but also intuition. The study sample comprised all 789,712 abstracts in English for case reports contained in the database PUBMED for the period 1 January 1983 to 31 December 2012. It was hypothesised that, if evidence and intuition concepts were viewed by these clinical authors as essential to understanding their case reports, they would be more likely to be found in the abstracts. Computational linguistics software was used in 1) concept mapping of 21,631,481 instances of 201 concepts, and 2) specific concept analyses examining 200 paired co-occurrences for 'evidence' and research 'literature' concepts. 'Evidence' is a fundamentally patient-centred, intuitive concept linked to less common concepts about underlying processes, suspected disease mechanisms and diagnostic hunches. In contrast, the use of research literature in clinical reasoning is linked to more common reasoning concepts about specific knowledge and descriptions or presenting features of cases. 'Literature' is by far the most dominant concept, increasing in relevance since 2003, with an overall relevance of 13% versus 5% for 'evidence' which has remained static. The fact that the least present types of reasoning concepts relate to diagnostic hunches to do with underlying processes, such as what is suspected, raises questions about whether intuitive practitioner evidence-making, found in a constellation of dynamic, process concepts, has become less important. The study adds support to the existing corpus of research on clinical reasoning, by suggesting that intuition involves a complex constellation of concepts important to how the construct of evidence is understood. The list of concepts the study generated offers a basis for reflection on the nature of evidence in diagnostic reasoning and the importance of intuition to that reasoning.

A comparison of calls subjected to a malpractice claim versus 'normal calls' within the Swedish healthcare direct: a case-control study.

PubMed

Ernesäter, Annica; Engström, Maria; Winblad, Ulrika; Holmström, Inger K

2014-10-03

The purpose of this study is to compare communication patterns in calls subjected to a malpractice claim with matched controls. In many countries, telephone advice nursing is patients' first contact with healthcare. Telenurses' assessment of callers' symptoms and needs are based on verbal communication only, and problems with over-triage and under-triage have been reported. A total sample of all reported medical errors (n=33) during the period 2003-2010 within Swedish Healthcare Direct was retrieved. Corresponding calls were thereafter identified and collected as sound files from the manager in charge at the respective call centres. For technical reasons, calls from four of the cases were not possible to retrieve. For the present study, matched control calls (n=26) based on the patient's age, gender and main symptom presented by the caller were collected. Male patients were in majority (n=16), and the most common reasons for calling were abdominal pain (n=10) and chest pain (n=5). There were statistically significant differences between the communication in the cases and controls: telenurses used fewer open-ended medical questions (p<0.001) in the cases compared to the control calls; callers provided telenurses with more medical information in the control calls compared to the cases (p=0.001); and telenurses used more facilitation and patient activation activities in the control calls (p=0.034), such as back-channel response (p=0.001), compared to the cases. The present study shows that telenurses in malpractice claimed calls used more closed-ended questioning compared to those in control calls, who used more open-ended questioning and back-channel response, which provided them with richer medical descriptions and more information from the caller. Hence, these communicative techniques are important in addition to solid medical and nursing competence and sound decision aid systems. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Priority-setting and hospital strategic planning: a qualitative case study.

PubMed

Martin, Douglas; Shulman, Ken; Santiago-Sorrell, Patricia; Singer, Peter

2003-10-01

To describe and evaluate the priority-setting element of a hospital's strategic planning process. Qualitative case study and evaluation against the conditions of 'accountability for reasonableness' of a strategic planning process at a large urban university-affiliated hospital. The hospital's strategic planning process met the conditions of 'accountability for reasonableness' in large part. Specifically: the hospital based its decisions on reasons (both information and criteria) that the participants felt were relevant to the hospital; the number and type of participants were very extensive; the process, decisions and reasons were well communicated throughout the organization, using multiple communication vehicles; and the process included an ethical framework linked to an effort to evaluate and improve the process. However, there were opportunities to improve the process, particularly by giving participants more time to absorb the information relevant to priority-setting decisions, more time to take difficult decisions and some means to appeal or revise decisions. A case study linked to an evaluation using 'accountability for reasonableness' can serve to improve priority-setting in the context of hospital strategic planning.

The harms of enhancement and the conclusive reasons view.

PubMed

Douglas, Thomas

2015-01-01

Many critics of bioenhancement go to considerable lengths to establish the existence of reasons against pursuing bioenhancements but do little to establish the absence of reasons in favor. This suggests that they accept what Allen Buchanan has called the conclusive reasons view (CRV). According to this view, our reasons against bioenhancement are obviously decisive, so there is no need to balance them against countervailing reasons. Buchanan criticizes the CRV by showing that the reasons most commonly adduced against bioenhancement are not decisive, or, at least, not obviously so. In this article, I suggest that both Buchanan and the authors to whom he is responding underestimate the strength of the case for the CRV. There are, I argue, harm-based reasons against bioenhancement that provide stronger support to the CRV than the reasons that have most often been adduced by critics of enhancement. However, I then argue that even these harm-based reasons are not obviously decisive. Thus, I ultimately agree with Buchanan about the falsity of the CRV, though I disagree with him about the reasons for its falsity.

Script-theory virtual case: A novel tool for education and research.

PubMed

Hayward, Jake; Cheung, Amandy; Velji, Alkarim; Altarejos, Jenny; Gill, Peter; Scarfe, Andrew; Lewis, Melanie

2016-11-01

Context/Setting: The script theory of diagnostic reasoning proposes that clinicians evaluate cases in the context of an "illness script," iteratively testing internal hypotheses against new information eventually reaching a diagnosis. We present a novel tool for teaching diagnostic reasoning to undergraduate medical students based on an adaptation of script theory. We developed a virtual patient case that used clinically authentic audio and video, interactive three-dimensional (3D) body images, and a simulated electronic medical record. Next, we used interactive slide bars to record respondents' likelihood estimates of diagnostic possibilities at various stages of the case. Responses were dynamically compared to data from expert clinicians and peers. Comparative frequency distributions were presented to the learner and final diagnostic likelihood estimates were analyzed. Detailed student feedback was collected. Over two academic years, 322 students participated. Student diagnostic likelihood estimates were similar year to year, but were consistently different from expert clinician estimates. Student feedback was overwhelmingly positive: students found the case was novel, innovative, clinically authentic, and a valuable learning experience. We demonstrate the successful implementation of a novel approach to teaching diagnostic reasoning. Future study may delineate reasoning processes associated with differences between novice and expert responses.

WELDSMART: A vision-based expert system for quality control

NASA Technical Reports Server (NTRS)

Andersen, Kristinn; Barnett, Robert Joel; Springfield, James F.; Cook, George E.

1992-01-01

This work was aimed at exploring means for utilizing computer technology in quality inspection and evaluation. Inspection of metallic welds was selected as the main application for this development and primary emphasis was placed on visual inspection, as opposed to other inspection methods, such as radiographic techniques. Emphasis was placed on methodologies with the potential for use in real-time quality control systems. Because quality evaluation is somewhat subjective, despite various efforts to classify discontinuities and standardize inspection methods, the task of using a computer for both inspection and evaluation was not trivial. The work started out with a review of the various inspection techniques that are used for quality control in welding. Among other observations from this review was the finding that most weld defects result in abnormalities that may be seen by visual inspection. This supports the approach of emphasizing visual inspection for this work. Quality control consists of two phases: (1) identification of weld discontinuities (some of which may be severe enough to be classified as defects), and (2) assessment or evaluation of the weld based on the observed discontinuities. Usually the latter phase results in a pass/fail judgement for the inspected piece. It is the conclusion of this work that the first of the above tasks, identification of discontinuities, is the most challenging one. It calls for sophisticated image processing and image analysis techniques, and frequently ad hoc methods have to be developed to identify specific features in the weld image. The difficulty of this task is generally not due to limited computing power. In most cases it was found that a modest personal computer or workstation could carry out most computations in a reasonably short time period. Rather, the algorithms and methods necessary for identifying weld discontinuities were in some cases limited. The fact that specific techniques were finally developed and successfully demosntrated to work illustrates that the general approach taken here appears to be promising for commercial development of computerized quality inspection systems. Inspection based on these techniques may be used to supplement or substitute more elaborate inspection methods, such as x-ray inspections.

Case-based Reasoning for Automotive Engine Performance Tune-up

NASA Astrophysics Data System (ADS)

Vong, C. M.; Huang, H.; Wong, P. K.

2010-05-01

The automotive engine performance tune-up is greatly affected by the calibration of its electronic control unit (ECU). The ECU calibration is traditionally done by trial-and-error method. This traditional method consumes a large amount of time and money because of a large number of dynamometer tests. To resolve this problem, case based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA) [1, 2]. CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.

[Surgery of benign vocal fold lesions].

PubMed

Olthoff, A

2016-09-01

Surgical treatment of benign vocal fold lesions can be indicated for clinical or functional reasons. The principles of phonosurgery have to be maintained in either case. The appropriate phonosurgical technique depends on the type of vocal fold lesion. Depending on the findings, phonosurgery aims to maintain or improve voice quality. The evaluation of clinical and functional results includes indirect laryngoscopy, videostroboscopy, and voice analysis.

Positivity-preserving numerical schemes for multidimensional advection

NASA Technical Reports Server (NTRS)

Leonard, B. P.; Macvean, M. K.; Lock, A. P.

1993-01-01

This report describes the construction of an explicit, single time-step, conservative, finite-volume method for multidimensional advective flow, based on a uniformly third-order polynomial interpolation algorithm (UTOPIA). Particular attention is paid to the problem of flow-to-grid angle-dependent, anisotropic distortion typical of one-dimensional schemes used component-wise. The third-order multidimensional scheme automatically includes certain cross-difference terms that guarantee good isotropy (and stability). However, above first-order, polynomial-based advection schemes do not preserve positivity (the multidimensional analogue of monotonicity). For this reason, a multidimensional generalization of the first author's universal flux-limiter is sought. This is a very challenging problem. A simple flux-limiter can be found; but this introduces strong anisotropic distortion. A more sophisticated technique, limiting part of the flux and then restoring the isotropy-maintaining cross-terms afterwards, gives more satisfactory results. Test cases are confined to two dimensions; three-dimensional extensions are briefly discussed.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Technical Reports Server (NTRS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-01-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

Model-based monitoring and diagnosis of a satellite-based instrument

NASA Astrophysics Data System (ADS)

Bos, Andre; Callies, Jorg; Lefebvre, Alain

1995-05-01

For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

A Novel Method of Case Representation and Retrieval in CBR for E-Learning

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

Evidence for an inhibitory-control theory of the reasoning brain.

PubMed

Houdé, Olivier; Borst, Grégoire

2015-01-01

In this article, we first describe our general inhibitory-control theory and, then, we describe how we have tested its specific hypotheses on reasoning with brain imaging techniques in adults and children. The innovative part of this perspective lies in its attempt to come up with a brain-based synthesis of Jean Piaget's theory on logical algorithms and Daniel Kahneman's theory on intuitive heuristics.

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

Protection as care: moral reasoning and moral orientation among ethnically and socioeconomically diverse older women.

PubMed

Dakin, Emily

2014-01-01

This study examined moral reasoning among ethnically and socioeconomically diverse older women based on the care and justice moral orientations reflecting theoretical frameworks developed by Carol Gilligan and Lawrence Kohlberg, respectively. A major gap in this area of research and theory development has been the lack of examination of moral reasoning in later life. This study addressed this gap by assessing socioeconomically and ethnically diverse older women's reasoning in response to ethical dilemmas showing conflict between autonomy, representative of Kohlberg's justice orientation, and protection, representative of Gilligan's care orientation. The dilemmas used in this study came from adult protective services (APS), the U.S. system that investigates and intervenes in cases of elder abuse and neglect. Subjects were 88 African American, Latina, and Caucasian women age 60 or over from varying socioeconomic status backgrounds who participated in eight focus groups. Overall, participants favored protection over autonomy in responding to the case scenarios. Their reasoning in responding to these dilemmas reflected an ethic of care and responsibility and a recognition of the limitations of autonomy. This reasoning is highly consistent with the care orientation. Variations in the overall ethic of care and responsibility based on ethnicity and SES also are discussed. Copyright © 2013. Published by Elsevier Inc.

Discovering relevance knowledge in data: a growing cell structures approach.

PubMed

Azuaje, F; Dubitzky, W; Black, N; Adamson, K

2000-01-01

Both information retrieval and case-based reasoning systems rely on effective and efficient selection of relevant data. Typically, relevance in such systems is approximated by similarity or indexing models. However, the definition of what makes data items similar or how they should be indexed is often nontrivial and time-consuming. Based on growing cell structure artificial neural networks, this paper presents a method that automatically constructs a case retrieval model from existing data. Within the case-based reasoning (CBR) framework, the method is evaluated for two medical prognosis tasks, namely, colorectal cancer survival and coronary heart disease risk prognosis. The results of the experiments suggest that the proposed method is effective and robust. To gain a deeper insight and understanding of the underlying mechanisms of the proposed model, a detailed empirical analysis of the models structural and behavioral properties is also provided.

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2011 CFR

2011-01-01

... fuels other than biodiesel blends and biomass-based diesel blends, you must possess a reasonable basis... alternative liquid automotive fuel that you must disclose. In the case of biodiesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biodiesel contained in...

Male/Female Differences in Perceptions and Effects of Hostile Environment Sexual Harassment: "Reasonable" Assumptions?

ERIC Educational Resources Information Center

Thacker, Rebecca A.; Gohmann, Stephen F.

1993-01-01

Discusses the "reasonable woman" standard in sexual harassment cases and gender-based differences in defining harassment. Investigates the issue of these differences in the emotional and psychological effects of hostile environments, using data from a survey of 8,523 public employees. (SK)

Developing a framework for qualitative engineering: Research in design and analysis of complex structural systems

NASA Technical Reports Server (NTRS)

Franck, Bruno M.

1990-01-01

The research is focused on automating the evaluation of complex structural systems, whether for the design of a new system or the analysis of an existing one, by developing new structural analysis techniques based on qualitative reasoning. The problem is to identify and better understand: (1) the requirements for the automation of design, and (2) the qualitative reasoning associated with the conceptual development of a complex system. The long-term objective is to develop an integrated design-risk assessment environment for the evaluation of complex structural systems. The scope of this short presentation is to describe the design and cognition components of the research. Design has received special attention in cognitive science because it is now identified as a problem solving activity that is different from other information processing tasks (1). Before an attempt can be made to automate design, a thorough understanding of the underlying design theory and methodology is needed, since the design process is, in many cases, multi-disciplinary, complex in size and motivation, and uses various reasoning processes involving different kinds of knowledge in ways which vary from one context to another. The objective is to unify all the various types of knowledge under one framework of cognition. This presentation focuses on the cognitive science framework that we are using to represent the knowledge aspects associated with the human mind's abstraction abilities and how we apply it to the engineering knowledge and engineering reasoning in design.

GhostWriter-2.0: Product Reviews with Case-Based Support

NASA Astrophysics Data System (ADS)

Bridge, Derek; Healy, Paul

A lot of user-generated content on the Web takes the form of records of personal experiences. Case-Based Reasoning offers a way of helping one user to reuse another's experiences from the Web. In this paper, we present GhostWriter-2.0, a Case-Based Reasoning system that supports a user who is writing a product review. GhostWriter-2.0 makes suggestions to the user, in the form of short phrases that are mined from other reviews. The purpose of the suggestions is to prompt the user to write a more comprehensive and helpful review than she might otherwise have done. We explain how GhostWriter-2.0's case base is populated with relevant and helpful reviews from Amazon. We show how it extracts and scores phrases in these reviews to decide which to suggest to the user.We report a trial with real users, in which users made greater use of GhostWriter-2.0's suggested phrases than they did of phrases suggested by a system that used a more random form of selection.

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

DTIC Science & Technology

1994-04-30

Learning Prototypical Cases OFF-BROADWAY, MCI and RMHC -* are three CBR-ML systems that learn case prototypes. We feel that methods that enable the...at Irvine Machine Learning Repository, including heart disease and breast cancer databases. OFF-BROADWAY, MCI and RMHC -* made the following notable

Building a case-based diet recommendation system without a knowledge engineer.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-02-01

We present a new approach to the effective development of menu construction systems that allow to automatically construct a menu that is strongly tailored to the individual requirements and food preferences of a client. In hospitals and other health care institutions dietitians develop diets for clients which need to change their eating habits. Many clients have special needs in regards to their medical conditions, cultural backgrounds, or special levels of nutrient requirements for better recovery from diseases or surgery, etc. Existing computer support for this task is insufficient-many diets are not specifically tailored for the client's needs or require substantial time of a dietitian to be manually developed. Our approach is based on case-based reasoning, an artificial intelligence technique that finds increasing entry into industrial practice. Our approach goes beyond the traditional case-based reasoning (CBR) approach by allowing an incremental improvement of the system's competency during routine use of the system. The improvement of the system takes place through a direct expert user-system interaction while the expert is accomplishing their tasks of constructing a diet for a given client. Whenever the system performs unsatisfactorily, the expert will need to modify the system-produced diet 'manually', i.e. by entering the desired modifications into the system. Our implemented system, menu construction using an incremental knowledge acquisition system (MIKAS), asks the expert for simple explanations for each of the manual actions he/she takes and incorporates the explanations automatically into its knowledge base (KB) so that the system will perform these manually conducted actions automatically at the next occasion. We present MIKAS and discuss the results of our case study. While still being a prototype, the senior clinical dietitian involved in our evaluation studies judges the approach to have considerable potential to improve the daily routine of hospital dietitians as well as to improve the average quality of the dietary advice given to patients within the limited available time for dietary consultations. Our approach opens up a new avenue towards building highly specialised CBR systems in a more cost-effective way. Hence, our approach promises to allow a significantly more widespread development and practical deployment of CBR systems in a large variety of application domains including many medical applications.

Simulation and experimental study of 802.11 based networking for vehicular management and safety.

DOT National Transportation Integrated Search

2009-03-01

This work focuses on the use of wireless networking techniques for their potential impact in providing : information for traffic management, control and public safety goals. The premise of this work is based on the : reasonable expectation that vehic...

On the radiated EMI current extraction of dc transmission line based on corona current statistical measurements

NASA Astrophysics Data System (ADS)

Yi, Yong; Chen, Zhengying; Wang, Liming

2018-05-01

Corona-originated discharge of DC transmission lines is the main reason for the radiated electromagnetic interference (EMI) field in the vicinity of transmission lines. A joint time-frequency analysis technique was proposed to extract the radiated EMI current (excitation current) of DC corona based on corona current statistical measurements. A reduced-scale experimental platform was setup to measure the statistical distributions of current waveform parameters of aluminum conductor steel reinforced. Based on the measured results, the peak value, root-mean-square value and average value with 9 kHz and 200 Hz band-with of 0.5 MHz radiated EMI current were calculated by the technique proposed and validated with conventional excitation function method. Radio interference (RI) was calculated based on the radiated EMI current and a wire-to-plate platform was built for the validity of the RI computation results. The reason for the certain deviation between the computations and measurements was detailed analyzed.

Air Pollution Instrumentation: A Trend toward Physical Methods

ERIC Educational Resources Information Center

Maugh, Thomas H., II

1972-01-01

Reviews reasons for the trend from wet chemical'' analytic techniques for measuring air pollutants toward physical methods based upon chemiluminescence, electrochemical transduction, flame ionization coupled with gas chromotography, and spectroscopy. (AL)

Case-based clinical reasoning in feline medicine: 3: Use of heuristics and illness scripts.

PubMed

Whitehead, Martin L; Canfield, Paul J; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-05-01

This is Article 3 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). In Article 2, published in the March 2016 issue, ways of managing cognitive error, particularly the negative impact of bias, in making a diagnosis were examined. This final article explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Case-based clinical reasoning in feline medicine: 2: Managing cognitive error.

PubMed

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-03-01

This is Article 2 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). This second article examines ways of managing cognitive error, particularly the negative impact of bias, when making a diagnosis. Article 3, to appear in the May 2016 issue, explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

Pectus excavatum repair from a plastic surgeon's perspective.

PubMed

Schwabegger, Anton H

2016-09-01

Minimally invasive repair of pectus excavatum (MIRPE) or similar procedures for pectus excavatum (PE) repair, nowadays no longer performed by one single speciality, may not always achieve sufficient aesthetic results, particularly in the infrapectoral or infraxiphoidal region. Reasons for this include the diaphragm inhibiting correct positioning of the bars, as well as asymmetric deformities which may still be present after remodelling attempts. Furthermore, some cases develop a mild recurrence or partial concavity once the correction bar is removed. However, any secondary re-do MIRPE procedure remains risky because of adhesions between the pleura, lung, pericardium, thoracic wall as residuals from the primary intervention. Treatment options as secondary correction for these deformities may include open access surgery, resection or reshaping of deformed costal cartilage. Moreover, augmentation of a residual concave area can be achieved by autologous transplantation of resected over-abundant cartilage, as well as by liposhifting or implantation of customized alloplastics. A physician dealing with PE corrections should be familiar with various shaping and complementary reconstructive techniques in order to provide the best options for a variety of expressions of anterior wall deformities. Among treating surgeons, there is an awareness that no single method can be applied for every kind of funnel chest deformity. An appropriate technique, either as a single approach for the ordinary deformities or in conjunction with ancillary procedures for the intricate cases, should be selected carefully based on the heterogeneity of symptoms, severity, expectations and surgical skill in addition to the available equipment. Out of a variety of such ancillary procedures available and based on experience within general plastic reconstructive surgery, some techniques for PE repair are explained and illustrated here with their advantages and disadvantages.

Missing Data in the Field of Otorhinolaryngology and Head & Neck Surgery: Need for Improvement.

PubMed

Netten, Anouk P; Dekker, Friedo W; Rieffe, Carolien; Soede, Wim; Briaire, Jeroen J; Frijns, Johan H M

Clinical studies are often facing missing data. Data can be missing for various reasons, for example, patients moved, certain measurements are only administered in high-risk groups, and patients are unable to attend clinic because of their health status. There are various ways to handle these missing data (e.g., complete cases analyses, mean substitution). Each of these techniques potentially influences both the analyses and the results of a study. The first aim of this structured review was to analyze how often researchers in the field of otorhinolaryngology/head & neck surgery report missing data. The second aim was to systematically describe how researchers handle missing data in their analyses. The third aim was to provide a solution on how to deal with missing data by means of the multiple imputation technique. With this review, we aim to contribute to a higher quality of reporting in otorhinolaryngology research. Clinical studies among the 398 most recently published research articles in three major journals in the field of otorhinolaryngology/head & neck surgery were analyzed based on how researchers reported and handled missing data. Of the 316 clinical studies, 85 studies reported some form of missing data. Of those 85, only a small number (12 studies, 3.8%) actively handled the missingness in their data. The majority of researchers exclude incomplete cases, which results in biased outcomes and a drop in statistical power. Within otorhinolaryngology research, missing data are largely ignored and underreported, and consequently, handled inadequately. This has major impact on the results and conclusions drawn from this research. Based on the outcomes of this review, we provide solutions on how to deal with missing data. To illustrate, we clarify the use of multiple imputation techniques, which recently became widely available in standard statistical programs.

Pectus excavatum repair from a plastic surgeon’s perspective

PubMed Central

2016-01-01

Minimally invasive repair of pectus excavatum (MIRPE) or similar procedures for pectus excavatum (PE) repair, nowadays no longer performed by one single speciality, may not always achieve sufficient aesthetic results, particularly in the infrapectoral or infraxiphoidal region. Reasons for this include the diaphragm inhibiting correct positioning of the bars, as well as asymmetric deformities which may still be present after remodelling attempts. Furthermore, some cases develop a mild recurrence or partial concavity once the correction bar is removed. However, any secondary re-do MIRPE procedure remains risky because of adhesions between the pleura, lung, pericardium, thoracic wall as residuals from the primary intervention. Treatment options as secondary correction for these deformities may include open access surgery, resection or reshaping of deformed costal cartilage. Moreover, augmentation of a residual concave area can be achieved by autologous transplantation of resected over-abundant cartilage, as well as by liposhifting or implantation of customized alloplastics. A physician dealing with PE corrections should be familiar with various shaping and complementary reconstructive techniques in order to provide the best options for a variety of expressions of anterior wall deformities. Among treating surgeons, there is an awareness that no single method can be applied for every kind of funnel chest deformity. An appropriate technique, either as a single approach for the ordinary deformities or in conjunction with ancillary procedures for the intricate cases, should be selected carefully based on the heterogeneity of symptoms, severity, expectations and surgical skill in addition to the available equipment. Out of a variety of such ancillary procedures available and based on experience within general plastic reconstructive surgery, some techniques for PE repair are explained and illustrated here with their advantages and disadvantages. PMID:27747184

Major Anthropogenic Causes for and Outcomes of Wild Animal Presentation to a Wildlife Clinic in East Tennessee, USA, 2000–2011

PubMed Central

Schenk, Ashley N.; Souza, Marcy J.

2014-01-01

To determine the reasons for presentation and outcome of wildlife cases in East Tennessee, a retrospective analysis was performed using 14,303 records from cases presented to the wildlife clinic of the University of Tennessee Veterinary Teaching Hospital between 2000 and 2011. The cases were first categorized into amphibian/non-avian reptile, mammal, or avian and then classified into groups based on the primary admitting/presenting sign. There are a variety of reasons animals were presented to the clinic, and some were directly or indirectly anthropogenic in origin, including cat related, dog related, hit by automobile, and other human encounters leading to trauma; of the cases reviewed, 4,443 (31.1%) presented for one of these 4 reasons. Overall case fatality risk in regard to these 4 admitting/presenting signs was 0.519 for the amphibian/non-avian reptile cases, 0.675 for mammal cases, and 0.687 for avian cases. This study confirms the importance of monitoring wildlife morbidity and mortality and of focusing efforts to reduce the anthropogenic threat on native habitats and resident wildlife populations. PMID:24686490

Unicompartmental knee arthroplasty modes of failure: wear is not the main reason for failure: a multicentre study of 418 failed knees.

PubMed

Epinette, J-A; Brunschweiler, B; Mertl, P; Mole, D; Cazenave, A

2012-10-01

This study originated from a symposium held by the French Hip and Knee Society (Société française de la hanche et du genou [SFHG]) and was carried out to better assess the distribution of causes of unicompartmental knee arthroplasty (UKA) failures, as well as cause-specific delay to onset. Our working hypothesis was that most failures were traceable to wear occurring over a period of many years. A multicentre retrospective study (25 centres) was conducted in 418 failed UKAs performed between 1978 and 2009. We determined the prevalence and time to onset of the main reasons for revision surgery based upon available preoperative findings. Additional intraoperative findings were analysed. The results were compared to those of nation wide registries to evaluate the representativeness of our study population. Times to revision surgery were short: 19% of revisions occurred within the first year and 48.5% within the first 5 years. Loosening was the main reason for failure (45%), followed by osteoarthritis progression (15%) and, finally, by wear (12%). Other reasons were technical problems in 11.5% of cases, unexplained pain in 5.5%, and failure of the supporting bone in 3.6%. The infection rate was 1.9%. Our results were consistent with those of Swedish and Australian registries. Our hypothesis was not confirmed. The short time to failure in most cases suggests a major role for surgical technique issues. Morbidity related to the implant per se may be seen as moderate and not greater than with total knee prostheses. The good agreement between our data and those of nationwide registries indicates that our population was representative. A finer analysis is needed, indicating that the establishment of a French registry would be of interest. Copyright © 2012. Published by Elsevier Masson SAS.

A juridical review of partnership agreements that have the elements of work agreements in Indonesia

NASA Astrophysics Data System (ADS)

Nugroho, A.; Sulistyowati, E.; Hikmah, N.

2018-01-01

The Partnership Agreements place the parties in an equal position each party has something as the bargaining power. In some cases, employers prefer to use Partnership Agreements to some individuals to complete the work in their company than Work agreements. Practicality and the absence of obligations to fulfil workers’ rights such as the right to join a Union and to get social security are some of the reasons why employers use the Partnership Agreements. Sometimes Partnership Agreement contains jobs, wages and orders which is the characteristic of work agreement. Based on the fact above, the legal issues arise whether the Partnership Agreement can be considered as the Work Agreement or not and which court is authorized to hear in the event of a dispute. To analyze the above legal issues, this research uses normative legal research type with the statute approach. The technique of legal material analysis uses prescriptive techniques to assess the issue and make recommendations. Based on the analysis, it can be concluded that the Partnership Agreement, of which the elements are: wages and orders can be categorized as Work Agreement and therefore in the event of a dispute, the authorized court is Industrial Relations Court.

Emotional reasoning and parent-based reasoning in non-clinical children, and their prospective relationships with anxiety symptoms.

PubMed

Morren, Mattijn; Muris, Peter; Kindt, Merel; Schouten, Erik; van den Hout, Marcel

2008-12-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based reasoning with anxiety symptoms in a sample of non-clinical children aged 8-14 years (n = 122). Children completed the anxiety subscales of the Revised Children's Anxiety and Depression Scale (Muris et al. Clin Psychol Psychother 9:430-442, 2002) and provided danger ratings of scenarios that systematically combined objective danger and objective safety information with anxiety-response and positive-response information. These measurements were repeated 10 months later (range 8-11 months). Emotional and parent-based reasoning effects emerged on both occasions. In addition, both effects were modestly stable, but only in case of objective safety. Evidence was found that initial anxiety levels were positively related to emotional reasoning 10 months later. In addition, initial levels of emotional reasoning were positively related to anxiety at a later time, but only when age was taken into account. That is, this relationship changed with increasing age from positive to negative. No significant prospective relationships emerged between anxiety and parent-based reasoning. As yet the clinical implications of these findings are limited, although preliminary evidence indicates that interpretation bias can be modified to decrease anxiety.

11 CFR 9036.4 - Commission review of submissions.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., in conducting its review, may utilize statistical sampling techniques. Based on the results of its... nonmatchable and the reason that it is not matchable; or if statistical sampling is used, the estimated amount...

Evidence for an inhibitory-control theory of the reasoning brain

PubMed Central

Houdé, Olivier; Borst, Grégoire

2015-01-01

In this article, we first describe our general inhibitory-control theory and, then, we describe how we have tested its specific hypotheses on reasoning with brain imaging techniques in adults and children. The innovative part of this perspective lies in its attempt to come up with a brain-based synthesis of Jean Piaget’s theory on logical algorithms and Daniel Kahneman’s theory on intuitive heuristics. PMID:25852528

Development of Reasoning Test Instruments Based on TIMSS Framework for Measuring Reasoning Ability of Senior High School Student on the Physics Concept

NASA Astrophysics Data System (ADS)

Muslim; Suhandi, A.; Nugraha, M. G.

2017-02-01

The purposes of this study are to determine the quality of reasoning test instruments that follow the framework of Trends in International Mathematics and Science Study (TIMSS) as a development results and to analyse the profile of reasoning skill of senior high school students on physics materials. This research used research and development method (R&D), furthermore the subject were 104 students at three senior high schools in Bandung selected by random sampling technique. Reasoning test instruments are constructed following the TIMSS framework in multiple choice forms in 30 questions that cover five subject matters i.e. parabolic motion and circular motion, Newton’s law of gravity, work and energy, harmonic oscillation, as well as the momentum and impulse. The quality of reasoning tests were analysed using the Content Validity Ratio (CVR) and classic test analysis include the validity of item, level of difficulty, discriminating power, reliability and Ferguson’s delta. As for the students’ reasoning skills profiles were analysed by the average score of achievements on eight aspects of the reasoning TIMSS framework. The results showed that reasoning test have a good quality as instruments to measure reasoning skills of senior high school students on five matters physics which developed and able to explore the reasoning of students on all aspects of reasoning based on TIMSS framework.

Fertility-preservation counselling and treatment for medical reasons: data from a multinational network of over 5000 women.

PubMed

von Wolff, Michael; Dittrich, Ralf; Liebenthron, Jana; Nawroth, Frank; Schüring, Andreas N; Bruckner, Thomas; Germeyer, Ariane

2015-11-01

Fertility-preservation techniques for medical reasons are increasingly offered in national networks. Knowledge of the characteristics of counselled patients and techniques used are essential. The FertiPROTEKT network registry was analysed between 2007 and 2013, and included up to 85 university and non-university centres in Germany, Austria and Switzerland; 5159 women were counselled and 4060 women underwent fertility preservation. In 2013, fertility-preservation counselling for medical reasons increased significantly among nullipara and women aged between 21 and 35 years (n = 1043; P < 0.001). Frequency of GnRH applications slowly decreased, whereas tissue, oocytes and zygote cryopreservation increased. In 2013, women with breast cancer mainly opted for tissue freezing, whereas women with lymphoma opted for GnRH agonist. Women younger than 20 years predominantly opted for GnRH agonists and ovarian tissue cryopreservation; women aged between 20 and 40 years underwent a variety of techniques; and women over 40 years opted for GnRH agonists. The average number of aspirated oocytes per stimulation cycle decreased as age increased (< 30 years: 12.9; 31-35 years: 12.3; 36-46: 9.0; > 41 years: 5.7). For ovarian tissue cryopreservation, removal and cryopreservation of fewer than one ovary was preferred and carried out in 97% of cases in 2013. Copyright © 2015 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

ERIC Educational Resources Information Center

Tawfik, Andrew A.; Alhoori, Hamed; Keene, Charles Wayne; Bailey, Christian; Hogan, Maureen

2018-01-01

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded…

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modelling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-10-01

Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prospecting area in northwestern Iran. The geophysical survey resulting in the ground magnetic data was conducted for magnetic element exploration. Firstly, the RTP technique was applied to recognize underground magnetic anomalies. RTP anomalies were classified into different populations based on the current method. For this reason, drilling point area determination by the RTP technique was complicated for magnetic anomalies, which are in the center and north of the studied area. Next, the C-A method was applied to the RTP magnetic anomalies (RTP-MA) to demonstrate magnetic susceptibility concentrations. This identification was appropriate for increasing the resolution of the drilling point area determination and decreasing the drilling risk issue, due to the economic costs of underground prospecting. In this study, the results of C-A modelling on the RTP-MA are compared with 8 borehole data. The results show that there is a good correlation between anomalies derived via the C-A method and the log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentrations, based on multifractal modelling data analyses, between 63 533.1 and 66 296 nT. Drilling results showed appropriate magnetite thickness with grades greater than 20 % Fe. The total associated with anomalies containing andesite units hosts iron mineralization.

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

PubMed Central

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

Elderly Healthcare Monitoring Using an Avatar-Based 3D Virtual Environment

PubMed Central

Pouke, Matti; Häkkilä, Jonna

2013-01-01

Homecare systems for elderly people are becoming increasingly important due to both economic reasons as well as patients’ preferences. Sensor-based surveillance technologies are an expected future trend, but research so far has devoted little attention to the User Interface (UI) design of such systems and the user-centric design approach. In this paper, we explore the possibilities of an avatar-based 3D visualization system, which exploits wearable sensors and human activity simulations. We present a technical prototype and the evaluation of alternative concept designs for UIs based on a 3D virtual world. The evaluation was conducted with homecare providers through focus groups and an online survey. Our results show firstly that systems taking advantage of 3D virtual world visualization techniques have potential especially due to the privacy preserving and simplified information presentation style, and secondly that simple representations and glancability should be emphasized in the design. The identified key use cases highlight that avatar-based 3D presentations can be helpful if they provide an overview as well as details on demand. PMID:24351747

The prediction of the cavitation phenomena including population balance modeling

NASA Astrophysics Data System (ADS)

Bannari, Rachid; Hliwa, Ghizlane Zineb; Bannari, Abdelfettah; Belghiti, Mly Taib

2017-07-01

Cavitation is the principal reason behind the behavior's modification of the hydraulic turbines. However, the experimental observations can not be appropriate to all cases due to the limitations in the measurement techniques. The mathematical models which have been implemented, use the mixture multiphase frame. As well as, most of the published work is limited by considering a constant bubble size distribution. However, this assumption is not realist. The aim of this article is the implementation and the use of a non-homogeneous multiphase model which solve two phases transport equation. The evolution of bubble size is considered by the population balance equation. This study is based on the eulerian-eulerian model, associated to the cavitation model. All the inter-phase forces such as drag, lift and virtual mass are used.

Power Law Versus Exponential Form of Slow Crack Growth of Advanced Structural Ceramics: Dynamic Fatigue

NASA Technical Reports Server (NTRS)

Choi, Sung R.; Gyekenyesi, John P.

2002-01-01

The life prediction analysis based on an exponential crack velocity formulation was examined using a variety of experimental data on glass and advanced structural ceramics in constant stress-rate ("dynamic fatigue") and preload testing at ambient and elevated temperatures. The data fit to the strength versus In (stress rate) relation was found to be very reasonable for most of the materials. It was also found that preloading technique was equally applicable for the case of slow crack growth (SCG) parameter n > 30. The major limitation in the exponential crack velocity formulation, however, was that an inert strength of a material must be known priori to evaluate the important SCG parameter n, a significant drawback as compared to the conventional power-law crack velocity formulation.

Immunology-Based Techniques for the Detection of Veterinary Drug Residues in Foods

NASA Astrophysics Data System (ADS)

Reig, Milagro; Toldrá, Fidel

Veterinary drugs are used in farm animals, via the feed or the drinking water, to prevent the outbreak of diseases or even for the treatment of diseases. However, the growth of animals may be promoted through the use of hormones and antibiotics. Depending on the type of residue and the application and washing conditions, these substances or its metabolites may remain in meat and other foods of animal origin and may cause adverse effects on consumers’ health. This is the main reason why its use is strictly regulated or even banned (case of the European Union) in different countries. Antibiotics typically used for growth promotion include chloramphenicol, nitrofurans, and enrofloxacin but others like sulphonamides, macrolides etc. may also be used (Reig & Toldrá, 2007).

An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources.

PubMed

Doulamis, A D; Doulamis, N D; Kollias, S D

2003-01-01

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.

[Reasons for consulting related to skin-bleaching products used by 104 women in Brazzaville].

PubMed

Gathse, A; Obengui; Ibara, J R

2005-12-01

A prospective survey has been carried out in the Brazzaville (Congo) dermatology service in order to specify dermatosis linked to the use of bleaching agents in 104 Congolese women consulting for this problem. The used bleaching agents were topical corticoids based products for 40 cases, hydroquinone for 32 cases, and hydroquinone associated with topical dermocorticoids for 32 cases. Acne was the most frequent motive for consulting (24%), followed by the paradoxical peri-orbital hyperpigmentation (21.1%), profuse mycosis (16.3%) and vibices(8.6%). The results of this survey were not superimposable to those of Dakar where infectious dermatosis were the first reason for consulting.

Simplified Estimation and Testing in Unbalanced Repeated Measures Designs.

PubMed

Spiess, Martin; Jordan, Pascal; Wendt, Mike

2018-05-07

In this paper we propose a simple estimator for unbalanced repeated measures design models where each unit is observed at least once in each cell of the experimental design. The estimator does not require a model of the error covariance structure. Thus, circularity of the error covariance matrix and estimation of correlation parameters and variances are not necessary. Together with a weak assumption about the reason for the varying number of observations, the proposed estimator and its variance estimator are unbiased. As an alternative to confidence intervals based on the normality assumption, a bias-corrected and accelerated bootstrap technique is considered. We also propose the naive percentile bootstrap for Wald-type tests where the standard Wald test may break down when the number of observations is small relative to the number of parameters to be estimated. In a simulation study we illustrate the properties of the estimator and the bootstrap techniques to calculate confidence intervals and conduct hypothesis tests in small and large samples under normality and non-normality of the errors. The results imply that the simple estimator is only slightly less efficient than an estimator that correctly assumes a block structure of the error correlation matrix, a special case of which is an equi-correlation matrix. Application of the estimator and the bootstrap technique is illustrated using data from a task switch experiment based on an experimental within design with 32 cells and 33 participants.

Detection and Tracking Based on a Dynamical Hierarchical Occupancy Map in Agent-Based Simulations

DTIC Science & Technology

2008-09-01

describes various techniques for targeting with probabilty reasoning. Advantages and disadvantages of the different methods will be discussed...Psum. Such an algorithm could decrease the performance of the prototype itself and therefore was not considered. Probabilty over time 0 0.2 0.4 0.6

A review of experimental and modeling techniques to determine properties of biopolymer-based nanocomposites

USDA-ARS?s Scientific Manuscript database

The nonbiodegradable and nonrenewable nature of plastic packaging has led to a renewed interest in packaging materials based on bio-nanocomposites (biopolymer matrix reinforced with nanoparticles such as layered silicates). One of the reasons for unique properties of bio-nanocomposites is the differ...

Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

NASA Technical Reports Server (NTRS)

Stephan, Amy; Erikson, Carol A.

1991-01-01

As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

Combination of laser-induced breakdown spectroscopy and Raman spectroscopy for multivariate classification of bacteria

NASA Astrophysics Data System (ADS)

Prochazka, D.; Mazura, M.; Samek, O.; Rebrošová, K.; Pořízka, P.; Klus, J.; Prochazková, P.; Novotný, J.; Novotný, K.; Kaiser, J.

2018-01-01

In this work, we investigate the impact of data provided by complementary laser-based spectroscopic methods on multivariate classification accuracy. Discrimination and classification of five Staphylococcus bacterial strains and one strain of Escherichia coli is presented. The technique that we used for measurements is a combination of Raman spectroscopy and Laser-Induced Breakdown Spectroscopy (LIBS). Obtained spectroscopic data were then processed using Multivariate Data Analysis algorithms. Principal Components Analysis (PCA) was selected as the most suitable technique for visualization of bacterial strains data. To classify the bacterial strains, we used Neural Networks, namely a supervised version of Kohonen's self-organizing maps (SOM). We were processing results in three different ways - separately from LIBS measurements, from Raman measurements, and we also merged data from both mentioned methods. The three types of results were then compared. By applying the PCA to Raman spectroscopy data, we observed that two bacterial strains were fully distinguished from the rest of the data set. In the case of LIBS data, three bacterial strains were fully discriminated. Using a combination of data from both methods, we achieved the complete discrimination of all bacterial strains. All the data were classified with a high success rate using SOM algorithm. The most accurate classification was obtained using a combination of data from both techniques. The classification accuracy varied, depending on specific samples and techniques. As for LIBS, the classification accuracy ranged from 45% to 100%, as for Raman Spectroscopy from 50% to 100% and in case of merged data, all samples were classified correctly. Based on the results of the experiments presented in this work, we can assume that the combination of Raman spectroscopy and LIBS significantly enhances discrimination and classification accuracy of bacterial species and strains. The reason is the complementarity in obtained chemical information while using these two methods.

Real-time threat assessment for critical infrastructure protection: data incest and conflict in evidential reasoning

NASA Astrophysics Data System (ADS)

Brandon, R.; Page, S.; Varndell, J.

2012-06-01

This paper presents a novel application of Evidential Reasoning to Threat Assessment for critical infrastructure protection. A fusion algorithm based on the PCR5 Dezert-Smarandache fusion rule is proposed which fuses alerts generated by a vision-based behaviour analysis algorithm and a-priori watch-list intelligence data. The fusion algorithm produces a prioritised event list according to a user-defined set of event-type severity or priority weightings. Results generated from application of the algorithm to real data and Behaviour Analysis alerts captured at London's Heathrow Airport under the EU FP7 SAMURAI programme are presented. A web-based demonstrator system is also described which implements the fusion process in real-time. It is shown that this system significantly reduces the data deluge problem, and directs the user's attention to the most pertinent alerts, enhancing their Situational Awareness (SA). The end-user is also able to alter the perceived importance of different event types in real-time, allowing the system to adapt rapidly to changes in priorities as the situation evolves. One of the key challenges associated with fusing information deriving from intelligence data is the issue of Data Incest. Techniques for handling Data Incest within Evidential Reasoning frameworks are proposed, and comparisons are drawn with respect to Data Incest management techniques that are commonly employed within Bayesian fusion frameworks (e.g. Covariance Intersection). The challenges associated with simultaneously dealing with conflicting information and Data Incest in Evidential Reasoning frameworks are also discussed.

Advantages of video trigger in problem-based learning.

PubMed

Chan, Lap Ki; Patil, Nivritti G; Chen, Julie Y; Lam, Jamie C M; Lau, Chak S; Ip, Mary S M

2010-01-01

Traditionally, paper cases are used as 'triggers' to stimulate learning in problem-based learning (PBL). However, video may be a better medium because it preserves the original language, encourages the active extraction of information, avoids depersonalization of patients and allows direct observation of clinical consultations. In short, it exposes the students to the complexity of actual clinical problems. The study aims to find out whether students and facilitators who are accustomed to paper cases would prefer video triggers or paper cases and the reasons for their preference. After students and facilitators had completed a video PBL tutorial, their responses were measured by a structured questionnaire using a modified Likert scale. A total of 257 students (92%) and 26 facilitators (100%) responded. The majority of students and facilitators considered that using video triggers could enhance the students' observational powers and clinical reasoning, help them to integrate different information and better understand the cases and motivate them to learn. They found PBL using video triggers more interesting and preferred it to PBL using paper cases. Video triggers are preferred by both students and facilitators over paper cases in PBL.

The pediatric mandible: II. Management of traumatic injury or fracture.

PubMed

Smartt, James M; Low, David W; Bartlett, Scott P

2005-08-01

After studying this article, the participant should be able to: 1. Describe the changing epidemiology of mandibular fractures in children and adolescents. 2. Discuss the appropriate use of internal fixation in the treatment of pediatric mandibular fractures. 3. Describe the difficulties posed by the deciduous dentition in the use of interdental wiring. 4. Understand reasons why techniques specific to adult fractures may not be applicable to the growing mandible. 5. Understand the etiology and epidemiology of pediatric mandibular fractures. 6. Understand the reasons for conservative (closed) versus aggressive (open) treatment of mandibular injury. Fractures of the pediatric mandible are complicated by the anatomic complexity of the developing mandible, particularly by the presence of tooth buds and the eruption of deciduous and permanent teeth. Traditional methods of fracture reduction and fixation employed in adults have little applicability in the pediatric population. The authors describe the surgical techniques that have been used at their institution and those that can be used safely in the pediatric setting. In most cases, "conservative" management is the preferred option, especially in the treatment of condylar fractures. In cases requiring surgical intervention, interdental wiring, drop wires in combination with circummandibular wires, and acrylic splints are suited well to specific phases of dental maturation. Open reduction and internal fixation using monocortical screws and microplates or resorbable plates and screws are acceptable techniques in the pediatric patient, but they require special safeguards. Algorithms are presented to simplify management of these complicated injuries.

Integrated low-intensity biofeedback therapy in fecal incontinence: evidence that "good" in-home anal sphincter exercise practice makes perfect.

PubMed

Vasant, D H; Solanki, K; Balakrishnan, S; Radhakrishnan, N V

2017-01-01

Biofeedback therapy (BFT) is an established treatment for fecal incontinence (FI), with access often being restricted to tertiary centers due to resources and the perceived requirement for high-intensity regimes. However, the optimal regime remains unknown. We evaluated outcomes from our low-intensity integrated BFT program in a secondary care center. Outcomes of our BFT service for FI were evaluated retrospectively. Response was defined by ≥50% improvement in FI frequency from baseline or complete continence. Responders were compared to non-responders for factors including symptoms, manometry data, sphincter exercise technique and duration of practice, and the number and frequency of sessions. Where patients dropped out, outcomes and the reason for dropout were obtained retrospectively. Fecal incontinence patients (n=205, median 62 years, 72% female) attended a median (IQR) 3 (2) BFT sessions with 55 (36) days between visits. Overall, 146/205 (71%) responded with 97/205 (47%) achieving continence. Fecal incontinence frequency improved dramatically in completed cases (P=0.000). While non-response was associated with males (P=0.03) and dropout (P=0.000), "good" anal sphincter exercise technique (P=0.008) and longer in-home practice (P=0.007) and more sessions (P=0.04) were associated with response. Dropout rate was 80/205 (39%), with the reason for dropout being obtained in 80%. Despite low-intensity BFT, comparable outcomes to data from tertiary centers were achieved. Our data emphasize the importance of technique and in-home practice of anal sphincter exercises. Customizing BFT intensity based on predictive factors and encouraging in-home practice may optimize outcomes, reduce dropout rates, and rationalize resources. © 2016 John Wiley & Sons Ltd.

Irrelevance Reasoning in Knowledge Based Systems

NASA Technical Reports Server (NTRS)

Levy, A. Y.

1993-01-01

This dissertation considers the problem of reasoning about irrelevance of knowledge in a principled and efficient manner. Specifically, it is concerned with two key problems: (1) developing algorithms for automatically deciding what parts of a knowledge base are irrelevant to a query and (2) the utility of relevance reasoning. The dissertation describes a novel tool, the query-tree, for reasoning about irrelevance. Based on the query-tree, we develop several algorithms for deciding what formulas are irrelevant to a query. Our general framework sheds new light on the problem of detecting independence of queries from updates. We present new results that significantly extend previous work in this area. The framework also provides a setting in which to investigate the connection between the notion of irrelevance and the creation of abstractions. We propose a new approach to research on reasoning with abstractions, in which we investigate the properties of an abstraction by considering the irrelevance claims on which it is based. We demonstrate the potential of the approach for the cases of abstraction of predicates and projection of predicate arguments. Finally, we describe an application of relevance reasoning to the domain of modeling physical devices.

Conflicting modes of reasoning in the Assisted Migration debate: a concept mapping analysis

NASA Astrophysics Data System (ADS)

Klenk, N. L.; Larson, B.

2011-12-01

A growing body of literature in biodiversity conservation and forestry has developed around the risks and benefits of the Assisted Migration (AM) of species, including recommendations for planning and management. However, despite years of academic debate, general consensus has yet to be reached between the proponents and the opponents of AM as a policy option. We hypothesize that the continued impasse arises out of fundamentally conflicting value judgments. Using a concept mapping technique, we analyzed reasons for and against AM, including the use of scientific evidence and the nature of the values and ethical norms that shape the modes of reasoning in the debate. Our results indicate the presence of a diversity of ethical arguments in addition to the standard precautionary argument and pragmatic reasoning. We further discovered that different kinds of scientific arguments are used by proponents versus opponents of AM: the former rely mostly on detailed biological and ecological facts about species most-at-risk under climate change, while the latter focus on broader ecological theories. Our analysis suggests little dispute over the scientific foundations of the debate. Instead, we suggest that the main barrier to consensus is the advocacy of fundamental values, which are a matter of personal choice, and thus not likely to be changed. One way out of this impasse is a pragmatic mode of reasoning, which eschews the debate on fundamental values and evaluates the means and ends of AM in a case-by-case approach.

University Teachers' Job Dissatisfaction: Application of Two-Factor Theory--A Case of Pakistani Education System

ERIC Educational Resources Information Center

Mir, Imran Anwar

2012-01-01

This qualitative case study presents the reasons of teachers' job dissatisfaction in the government educational institutes in Pakistan. This case study is based on the two factor theory of Herzberg. The results of this case study reveal four core factors that cause job dissatisfaction among teachers in the public sector universities in developing…

Plasmonic Biosensors

PubMed Central

Hill, Ryan T.

2015-01-01

The unique optical properties of plasmon resonant nanostructures enable exploration of nanoscale environments using relatively simple optical characterization techniques. For this reason, the field of plasmonics continues to garner the attention of the biosensing community. Biosensors based on propagating surface plasmon resonances (SPRs) in films are the most well-recognized plasmonic biosensors, but there is great potential for the new, developing technologies to surpass the robustness and popularity of film-based SPR sensing. This review surveys the current plasmonic biosensor landscape with emphasis on the basic operating principles of each plasmonic sensing technique and the practical considerations when developing a sensing platform with the various techniques. The “gold standard” film SPR technique is reviewed briefly, but special emphasis is devoted to the up-and-coming LSPR-based and plasmonically coupled sensor technology. PMID:25377594

Approximate spatial reasoning

NASA Technical Reports Server (NTRS)

Dutta, Soumitra

1988-01-01

Much of human reasoning is approximate in nature. Formal models of reasoning traditionally try to be precise and reject the fuzziness of concepts in natural use and replace them with non-fuzzy scientific explicata by a process of precisiation. As an alternate to this approach, it has been suggested that rather than regard human reasoning processes as themselves approximating to some more refined and exact logical process that can be carried out with mathematical precision, the essence and power of human reasoning is in its capability to grasp and use inexact concepts directly. This view is supported by the widespread fuzziness of simple everyday terms (e.g., near tall) and the complexity of ordinary tasks (e.g., cleaning a room). Spatial reasoning is an area where humans consistently reason approximately with demonstrably good results. Consider the case of crossing a traffic intersection. We have only an approximate idea of the locations and speeds of various obstacles (e.g., persons and vehicles), but we nevertheless manage to cross such traffic intersections without any harm. The details of our mental processes which enable us to carry out such intricate tasks in such apparently simple manner are not well understood. However, it is that we try to incorporate such approximate reasoning techniques in our computer systems. Approximate spatial reasoning is very important for intelligent mobile agents (e.g., robots), specially for those operating in uncertain or unknown or dynamic domains.

Repair of distal biceps tendon rupture with the Biotenodesis screw.

PubMed

Khan, W; Agarwal, M; Funk, L

2004-04-01

Distal biceps tendon ruptures are uncommon injuries with only around 300 cases reported in the literature. Current management tends to favour anatomical reinsertion of the tendon into the radial tuberosity, especially in young and active individuals. These injuries are commonly repaired using either a single anterior incision with suture anchors or the Boyd-Anderson dual incision technique. We report the use of a bioabsorbable interference screw for the repair of distal biceps tendon rupture using a minimal incision technique. In this technique the avulsed tendon and a bioabsorbable screw are secured in a drill hole on the radial tuberosity using whip stitch and fibre wire sutures according to Biotenodesis system guidelines. The technique described requires minimal volar dissection that is associated with a reduced number of synostosis and posterior interosseous nerve injuries. The bioabsorbable interference screw has all the advantages of being biodegradable and has been shown to have greater pullout strength than suture anchors. It is also a reasonable alternative to titanium screws in terms of primary fixation strength. The strong fixation provided allows early active motion and return to previous activities as seen in our case.

Fuzzy similarity measures for ultrasound tissue characterization

NASA Astrophysics Data System (ADS)

Emara, Salem M.; Badawi, Ahmed M.; Youssef, Abou-Bakr M.

1995-03-01

Computerized ultrasound tissue characterization has become an objective means for diagnosis of diseases. It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty liver from a normal one, by visual inspection from the ultrasound images. The visual criteria for differentiating diffused diseases is rather confusing and highly dependent upon the sonographer's experience. The need for computerized tissue characterization is thus justified to quantitatively assist the sonographer for accurate differentiation and to minimize the degree of risk from erroneous interpretation. In this paper we used the fuzzy similarity measure as an approximate reasoning technique to find the maximum degree of matching between an unknown case defined by a feature vector and a family of prototypes (knowledge base). The feature vector used for the matching process contains 8 quantitative parameters (textural, acoustical, and speckle parameters) extracted from the ultrasound image. The steps done to match an unknown case with the family of prototypes (cirr, fatty, normal) are: Choosing the membership functions for each parameter, then obtaining the fuzzification matrix for the unknown case and the family of prototypes, then by the linguistic evaluation of two fuzzy quantities we obtain the similarity matrix, then by a simple aggregation method and the fuzzy integrals we obtain the degree of similarity. Finally, we find that the similarity measure results are comparable to the neural network classification techniques and it can be used in medical diagnosis to determine the pathology of the liver and to monitor the extent of the disease.

Modular expert system for the diagnosis of operating conditions of industrial anaerobic digestion plants.

PubMed

Lardon, L; Puñal, A; Martinez, J A; Steyer, J P

2005-01-01

Anaerobic digestion (AD) plants are highly efficient wastewater treatment processes with possible energetic valorisation. Despite these advantages, many industries are still reluctant to use them because of their instability in the face of changes in operating conditions. To the face this drawback and to enhance the industrial use of anaerobic digestion, one solution is to develop and to implement knowledge base (KB) systems that are able to detect and to assess in real-time the quality of operating conditions of the processes. Case-based techniques and heuristic approaches have been already tested and validated on AD processes but two major properties were lacking: modularity of the system (the knowledge base system should be easily tuned on a new process and should still work if one or more sensors are added or removed) and uncertainty management (the assessment of the KB system should remain relevant even in the case of too poor or conflicting information sources). This paper addresses these two points and presents a modular KB system where an uncertain reasoning formalism is used to combine partial and complementary fuzzy diagnosis modules. Demonstration of the interest of the approach is provided from real-life experiments performed on an industrial 2,000 m3 CSTR anaerobic digester.

iCBLS: An interactive case-based learning system for medical education.

PubMed

Ali, Maqbool; Han, Soyeon Caren; Bilal, Hafiz Syed Muhammad; Lee, Sungyoung; Kang, Matthew Jee Yun; Kang, Byeong Ho; Razzaq, Muhammad Asif; Amin, Muhammad Bilal

2018-01-01

Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world scenarios that need to be solved using their reasoning skills and existing theoretical knowledge. In this paper, we propose an interactive CBL System, called iCBLS, which supports the development of collaborative clinical reasoning skills for medical students in an online environment. The iCBLS consists of three modules: (i) system administration (SA), (ii) clinical case creation (CCC) with an innovative semi-automatic approach, and (iii) case formulation (CF) through intervention of medical students' and teachers' knowledge. Two evaluations under the umbrella of the context/input/process/product (CIPP) model have been performed with a Glycemia study. The first focused on the system satisfaction, evaluated by 54 students. The latter aimed to evaluate the system effectiveness, simulated by 155 students. The results show a high success rate of 70% for students' interaction, 76.4% for group learning, 72.8% for solo learning, and 74.6% for improved clinical skills. Copyright © 2017 Elsevier B.V. All rights reserved.

DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

PubMed Central

Golobardes, Elisabet; Corral, Guiomar; Puig, Susana; Malvehy, Josep

2014-01-01

The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosis has become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration of several multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis. PMID:24578629

What's in a Label? Is Diagnosis the Start or the End of Clinical Reasoning?

PubMed

Ilgen, Jonathan S; Eva, Kevin W; Regehr, Glenn

2016-04-01

Diagnostic reasoning has received substantial attention in the literature, yet what we mean by "diagnosis" may vary. Diagnosis can align with assignment of a "label," where a constellation of signs, symptoms, and test results is unified into a solution at a single point in time. This "diagnostic labeling" conceptualization is embodied in our case-based learning curricula, published case reports, and research studies, all of which treat diagnostic accuracy as the primary outcome. However, this conceptualization may oversimplify the richly iterative and evolutionary nature of clinical reasoning in many settings. Diagnosis can also represent a process of guiding one's thoughts by "making meaning" from data that are intrinsically dynamic, experienced idiosyncratically, negotiated among team members, and rich with opportunities for exploration. Thus, there are two complementary constructions of diagnosis: 1) the correct solution resulting from a diagnostic reasoning process, and 2) a dynamic aid to an ongoing clinical reasoning process. This article discusses the importance of recognizing these two conceptualizations of "diagnosis," outlines the unintended consequences of emphasizing diagnostic labeling as the primary goal of clinical reasoning, and suggests how framing diagnosis as an ongoing process of meaning-making might change how we think about teaching and assessing clinical reasoning.

Illness script development in pre-clinical education through case-based clinical reasoning training

PubMed Central

Keemink, Yvette; van Dijk, Savannah; ten Cate, Olle

2018-01-01

Objectives To assess illness script richness and maturity in preclinical students after they attended a specifically structured instructional format, i.e., a case based clinical reasoning (CBCR) course. Methods In a within-subject experimental design, medical students who had finished the CBCR course participated in an illness script experiment. In the first session, richness and maturity of students’ illness scripts for diseases discussed during the CBCR course were compared to illness script richness and maturity for similar diseases not included in the course. In the second session, diagnostic performance was tested, to test for differences between CBCR cases and non-CBCR cases. Scores on the CBCR course exam were related to both experimental outcomes. Results Thirty-two medical students participated. Illness script richness for CBCR diseases was almost 20% higher than for non-CBCR diseases, on average 14.47 (SD=3.25) versus 12.14 (SD=2.80), respectively (p<0.001). In addition, students provided more information on Enabling Conditions and less on Fault-related aspects of the disease. Diagnostic performance was better for the diseases discussed in the CBCR course, mean score 1.63 (SD=0.32) versus 1.15 (SD=0.29) for non-CBCR diseases (p<0.001). A significant correlation of exam results with recognition of CBCR cases was found (r=0.571, p<0.001), but not with illness script richness (r=–0.006, p=NS). Conclusions The CBCR-course fosters early development of clinical reasoning skills by increasing the illness script richness and diagnostic performance of pre-clinical students. However, these results are disease-specific and therefore we cannot conclude that students develop a more general clinical reasoning ability. PMID:29428911

Illness script development in pre-clinical education through case-based clinical reasoning training.

PubMed

Keemink, Yvette; Custers, Eugene J F M; van Dijk, Savannah; Ten Cate, Olle

2018-02-09

To assess illness script richness and maturity in preclinical students after they attended a specifically structured instructional format, i.e., a case based clinical reasoning (CBCR) course. In a within-subject experimental design, medical students who had finished the CBCR course participated in an illness script experiment. In the first session, richness and maturity of students' illness scripts for diseases discussed during the CBCR course were compared to illness script richness and maturity for similar diseases not included in the course. In the second session, diagnostic performance was tested, to test for differences between CBCR cases and non-CBCR cases. Scores on the CBCR course exam were related to both experimental outcomes. Thirty-two medical students participated. Illness script richness for CBCR diseases was almost 20% higher than for non-CBCR diseases, on average 14.47 (SD=3.25) versus 12.14 (SD=2.80), respectively (p<0.001). In addition, students provided more information on Enabling Conditions and less on Fault-related aspects of the disease. Diagnostic performance was better for the diseases discussed in the CBCR course, mean score 1.63 (SD=0.32) versus 1.15 (SD=0.29) for non-CBCR diseases (p<0.001). A significant correlation of exam results with recognition of CBCR cases was found (r=0.571, p<0.001), but not with illness script richness (r=-0.006, p=NS). The CBCR-course fosters early development of clinical reasoning skills by increasing the illness script richness and diagnostic performance of pre-clinical students. However, these results are disease-specific and therefore we cannot conclude that students develop a more general clinical reasoning ability.

The Edwin Smith papyrus: a clinical reappraisal of the oldest known document on spinal injuries

PubMed Central

Sanchez, Gonzalo M.; Burridge, Alwyn L.

2010-01-01

Dating from the seventeenth century b.c. the Edwin Smith papyrus is a unique treatise containing the oldest known descriptions of signs and symptoms of injuries of the spinal column and spinal cord. Based on a recent “medically based translation” of the Smith papyrus, its enclosed treasures in diagnostic, prognostic and therapeutic reasoning are revisited. Although patient demographics, diagnostic techniques and therapeutic options considerably changed over time, the documented rationale on spinal injuries can still be regarded as the state-of-the-art reasoning for modern clinical practice. PMID:20697750

Pins and Rubbers Traction System.

PubMed

de Soras, X; de Mourgues, P; Guinard, D; Moutet, F

1997-12-01

The Pins and Rubbers Traction System (PRTS) is a mobile frame created with wires to support elastic traction, which produces a ligamentotaxis effect in the same direction and of the same intensity whatever the position of the joint. This technique has been used in 11 cases of complex PIP joint fractures with eight excellent results. The advantages are simplicity, adaptability, the possibility of immediate mobilization, reasonable cost and relatively small bulk.

Vibrato in Singing Voice: The Link between Source-Filter and Sinusoidal Models

NASA Astrophysics Data System (ADS)

Arroabarren, Ixone; Carlosena, Alfonso

2004-12-01

The application of inverse filtering techniques for high-quality singing voice analysis/synthesis is discussed. In the context of source-filter models, inverse filtering provides a noninvasive method to extract the voice source, and thus to study voice quality. Although this approach is widely used in speech synthesis, this is not the case in singing voice. Several studies have proved that inverse filtering techniques fail in the case of singing voice, the reasons being unclear. In order to shed light on this problem, we will consider here an additional feature of singing voice, not present in speech: the vibrato. Vibrato has been traditionally studied by sinusoidal modeling. As an alternative, we will introduce here a novel noninteractive source filter model that incorporates the mechanisms of vibrato generation. This model will also allow the comparison of the results produced by inverse filtering techniques and by sinusoidal modeling, as they apply to singing voice and not to speech. In this way, the limitations of these conventional techniques, described in previous literature, will be explained. Both synthetic signals and singer recordings are used to validate and compare the techniques presented in the paper.

The Effects of the Refugee Crisis on Age Estimation Analysis over the Past 10 Years: A 16-Country Survey

PubMed Central

Sykes, Leanne; Bhayat, Ahmed; Bernitz, Herman

2017-01-01

Dental age estimation (AE) tests are routinely done on living and deceased persons. There is anecdotal evidence suggesting an increase in age estimations due to the refugee crisis. Our aim is to determine the reasons and methods for performing dental AE tests in both living and deceased individuals. Global trends in AE over the past 10 years were also investigated. A database of all forensic laboratories was obtained and an electronic questionnaire was sent to all of them. The questionnaire was self-developed and included questions on the reasons for performing AE tests, the preferred methods used in living and deceased individuals, and the people/organizations who requested these AE tests. The number of tests performed annually varied between 0 and 500 and the majority were on asylum seekers, refugees, and for adoption cases. Most units used multiple techniques to determine the age among the living, but seldom used more than three techniques for the deceased. The majority of tests were requested by coroners and the legal fraternity. There has been an increase in the number of dental AEs carried out and this has been mostly due to asylum seekers and refugees. The most common techniques for the living were variations of Demirjian’s technique while country specific techniques were used for the deceased. PMID:28608845

Use of Web-based training for quality improvement between a field immunohistochemistry laboratory in Nigeria and its United States-based partner institution.

PubMed

Oluwasola, Abideen O; Malaka, David; Khramtsov, Andrey Ilyich; Ikpatt, Offiong Francis; Odetunde, Abayomi; Adeyanju, Oyinlolu Olorunsogo; Sveen, Walmy Elisabeth; Falusi, Adeyinka Gloria; Huo, Dezheng; Olopade, Olufunmilayo Ibironke

2013-12-01

The importance of hormone receptor status in assigning treatment and the potential use of human epidermal growth factor receptor 2 (HER2)-targeted therapy have made it beneficial for laboratories to improve detection techniques. Because interlaboratory variability in immunohistochemistry (IHC) tests may also affect studies of breast cancer subtypes in different countries, we undertook a Web-based quality improvement training and a comparative study of accuracy of immunohistochemical tests of breast cancer biomarkers between a well-established laboratory in the United States (University of Chicago) and a field laboratory in Ibadan, Nigeria. Two hundred and thirty-two breast tumor blocks were evaluated for estrogen receptors (ERs), progesterone receptors (PRs), and HER2 status at both laboratories using tissue microarray technique. Initially, concordance analysis revealed κ scores of 0.42 (moderate agreement) for ER, 0.41 (moderate agreement) for PR, and 0.39 (fair agreement) for HER2 between the 2 laboratories. Antigen retrieval techniques and scoring methods were identified as important reasons for discrepancy. Web-based conferences using Web conferencing tools such as Skype and WebEx were then held periodically to discuss IHC staining protocols and standard scoring systems and to resolve discrepant cases. After quality assurance and training, the agreement improved to 0.64 (substantial agreement) for ER, 0.60 (moderate agreement) for PR, and 0.75 (substantial agreement) for HER2. We found Web-based conferences and digital microscopy useful and cost-effective tools for quality assurance of IHC, consultation, and collaboration between distant laboratories. Quality improvement exercises in testing of tumor biomarkers will reduce misclassification in epidemiologic studies of breast cancer subtypes and provide much needed capacity building in resource-poor countries. © 2013.

Anonymity and Historical-Anonymity in Location-Based Services

NASA Astrophysics Data System (ADS)

Bettini, Claudio; Mascetti, Sergio; Wang, X. Sean; Freni, Dario; Jajodia, Sushil

The problem of protecting user’s privacy in Location-Based Services (LBS) has been extensively studied recently and several defense techniques have been proposed. In this contribution, we first present a categorization of privacy attacks and related defenses. Then, we consider the class of defense techniques that aim at providing privacy through anonymity and in particular algorithms achieving “historical k- anonymity” in the case of the adversary obtaining a trace of requests recognized as being issued by the same (anonymous) user. Finally, we investigate the issues involved in the experimental evaluation of anonymity based defense techniques; we show that user movement simulations based on mostly random movements can lead to overestimate the privacy protection in some cases and to overprotective techniques in other cases. The above results are obtained by comparison to a more realistic simulation with an agent-based simulator, considering a specific deployment scenario.

Faith and reason and physician-assisted suicide.

PubMed

Kaczor, Christopher

1998-08-01

Aquinas's conception of the relationship of faith and reason calls into question the arguments and some of the conclusions advanced in contributions to the debate on physician-assisted suicide by David Thomasma and H. Tristram Engelhardt. An understanding of the nature of theology as based on revelation calls into question Thomasma's theological argument in favor of physician-assisted suicide based on the example of Christ and the martyrs. On the other hand, unaided reason calls into question his assumptions about the nature of death as in some cases a good for the human person. Finally, if Aquinas is right about the relationship of faith and reason, Engelhardt's sharp contrast between "Christian" and "secular" approaches to physician-assisted suicide needs reconsideration, although his conclusions about physician-assisted suicide would find support.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

A situated reasoning architecture for space-based repair and replace tasks

NASA Technical Reports Server (NTRS)

Bloom, Ben; Mcgrath, Debra; Sanborn, Jim

1989-01-01

Space-based robots need low level control for collision detection and avoidance, short-term load management, fine-grained motion, and other physical tasks. In addition, higher level control is required to focus strategic decision making as missions are assigned and carried out. Reasoning and control must be responsive to ongoing changes in the environment. Research aimed at bridging the gap between high level artificial intelligence (AI) planning techniques and task-level robot programming for telerobotic systems is described. Situated reasoning is incorporated into AI and Robotics systems in order to coordinate a robot's activity within its environment. An integrated system under development in a component maintenance domain is described. It is geared towards replacing worn and/or failed Orbital Replacement Units (ORUs) designed for use aboard NASA's Space Station Freedom based on the collection of components available at a given time. High level control reasons in component space in order to maximize the number operational component-cells over time, while the task-level controls sensors and effectors, detects collisions, and carries out pick and place tasks in physical space. Situated reasoning is used throughout the system to cope with component failures, imperfect information, and unexpected events.

The GIS map coloring support decision-making system based on case-based reasoning and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Deng, Shuang; Xiang, Wenting; Tian, Yangge

2009-10-01

Map coloring is a hard task even to the experienced map experts. In the GIS project, usually need to color map according to the customer, which make the work more complex. With the development of GIS, more and more programmers join the project team, which lack the training of cartology, their coloring map are harder to meet the requirements of customer. From the experience, customers with similar background usually have similar tastes for coloring map. So, we developed a GIS color scheme decision-making system which can select color schemes of similar customers from case base for customers to select and adjust. The system is a BS/CS mixed system, the client side use JSP and make it possible for the system developers to go on remote calling of the colors scheme cases in the database server and communicate with customers. Different with general case-based reasoning, even the customers are very similar, their selection may have difference, it is hard to provide a "best" option. So, we select the Simulated Annealing Algorithm (SAA) to arrange the emergence order of different color schemes. Customers can also dynamically adjust certain features colors based on existing case. The result shows that the system can facilitate the communication between the designers and the customers and improve the quality and efficiency of coloring map.

Three trepanned skulls from the Copacabana Peninsula in the Titicaca Basin, Bolivia (800 BC-AD 1000).

PubMed

Juengst, Sara L; Chávez, Sergio J

2015-06-01

This paper presents three trepanned skulls from the Copacabana Peninsula in the Titicaca Basin, dating from 800 BC to AD 1000. Trepanation has been practiced for two millennia in the Andes, with the earliest specimens coming from the coastal Paracas culture (circa 400 BC). Trepanned skulls have been found throughout the Andes, displaying a variety of techniques. This modification was practiced as surgical intervention after injury and treatment for headaches and other ailments, among other reasons (Verano, 2003: 234). With the exception of four examples from the Island of the Sun, few early cases of trepanation have been found in the Titicaca Basin of Peru and Bolivia. The three skulls presented here are important for several reasons: (1) they originate from a region under-represented in the literature on Andean trepanation, (2) they represent a variety of trepanation techniques, and (3) they confirm the practice of trepanation in the lake basin during the Early Horizon. Copyright © 2014 Elsevier Inc. All rights reserved.

Hybrid Systems Diagnosis

NASA Technical Reports Server (NTRS)

McIlraith, Sheila; Biswas, Gautam; Clancy, Dan; Gupta, Vineet

2005-01-01

This paper reports on an on-going Project to investigate techniques to diagnose complex dynamical systems that are modeled as hybrid systems. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. We cast the diagnosis problem as a model selection problem. To reduce the space of potential models under consideration, we exploit techniques from qualitative reasoning to conjecture an initial set of qualitative candidate diagnoses, which induce a smaller set of models. We refine these diagnoses using parameter estimation and model fitting techniques. As a motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

Defaults, context, and knowledge: alternatives for OWL-indexed knowledge bases.

PubMed

Rector, A

2004-01-01

The new Web Ontology Language (OWL) and its Description Logic compatible sublanguage (OWL-DL) explicitly exclude defaults and exceptions, as do all logic based formalisms for ontologies. However, many biomedical applications appear to require default reasoning, at least if they are to be engineered in a maintainable way. Default reasoning has always been one of the great strengths of Frame systems such as Protégé. Resolving this conflict requires analysis of the different uses for defaults and exceptions. In some cases, alternatives can be provided within the OWL framework; in others, it appears that hybrid reasoning about a knowledge base of contingent facts built around the core ontology is necessary. Trade-offs include both human factors and the scaling of computational performance. The analysis presented here is based on the OpenGALEN experience with large scale ontologies using a formalism, GRAIL, which explicitly incorporates constructs for hybrid reasoning, numerous experiments with OWL, and initial work on combining OWL and Protégé.

[Psychological debriefing and post-immediate psychotherapeutic intervention].

PubMed

Prieto, Nathalie; Cheucle, Eric; Meylan, Françoise

2010-01-01

Psychological debriefing is a controversial treatment technique. In principle, many such treatments exist based on apparently indisputable conclusions which only assess the personal traumatic effect and neglect the collective impact, which is the original reason for the creation of this technique. Therefore, it is essential to take a look at the way in which debriefings are conducted, its indications, its limits and the psychodynamic processes at play.

Web-Based Trainer for Electrical Circuit Analysis

ERIC Educational Resources Information Center

Weyten, L.; Rombouts, P.; De Maeyer, J.

2009-01-01

A Web-based system for training electric circuit analysis is presented in this paper. It is centered on symbolic analysis techniques and it not only verifies the student's final answer, but it also tracks and coaches him/her through all steps of his/her reasoning path. The system mimics homework assignments, enhanced by immediate personalized…

PDA: A coupling of knowledge and memory for case-based reasoning

NASA Technical Reports Server (NTRS)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques.

PubMed

Bölling, Christian; Weidlich, Michael; Holzhütter, Hermann-Georg

2014-01-01

Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats.

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

PubMed

Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

PubMed

El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

2015-11-01

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

PubMed

Schmidt, Rainer; Gierl, Lothar

2005-03-01

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

Effects of alternative outcome scenarios and structured outcome evaluation on case-based ethics instruction.

PubMed

Peacock, Juandre; Harkrider, Lauren N; Bagdasarov, Zhanna; Connelly, Shane; Johnson, James F; Thiel, Chase E; Macdougall, Alexandra E; Mumford, Michael D; Devenport, Lynn D

2013-09-01

Case-based instruction has been regarded by many as a viable alternative to traditional lecture-based education and training. However, little is known about how case-based training techniques impact training effectiveness. This study examined the effects of two such techniques: (a) presentation of alternative outcome scenarios to a case, and (b) conducting a structured outcome evaluation. Consistent with the hypotheses, results indicate that presentation of alternative outcome scenarios reduced knowledge acquisition, reduced sensemaking and ethical decision-making strategy use, and reduced decision ethicality. Conducting a structured outcome evaluation had no impact on these outcomes. Results indicate that those who use case-based instruction should take care to use clear, less complex cases with only a singular outcome if they are seeking these types of outcomes.

INCORPORATING NONCHEMICAL STRESSORS INTO CUMMULATIVE RISK ASSESSMENTS

EPA Science Inventory

The risk assessment paradigm has begun to shift from assessing single chemicals using "reasonable worst case" assumptions for individuals to considering multiple chemicals and community-based models. Inherent in community-based risk assessment is examination of all stressors a...

Evolution of Students' Reasoning Skills on a Two Year Basis in a PBL Curriculum in Medicine.

ERIC Educational Resources Information Center

Bedard, Denis; And Others

A 2-year study at the University of Sherbrooke (Quebec) investigated the changes in six medical students' clinical reasoning processes as they participated in a problem-based learning (PBL) curriculum. In each year, students performed a think-aloud protocol with two medical case problems to solve, one in cardiology and one in urology. In the…

Student perception of two different simulation techniques in oral and maxillofacial surgery undergraduate training.

PubMed

Lund, Bodil; Fors, Uno; Sejersen, Ronny; Sallnäs, Eva-Lotta; Rosén, Annika

2011-10-12

Yearly surveys among the undergraduate students in oral and maxillofacial surgery at Karolinska Institutet have conveyed a wish for increased clinical training, and in particular, in surgical removal of mandibular third molars. Due to lack of resources, this kind of clinical supervision has so far not been possible to implement. One possible solution to this problem might be to introduce simulation into the curriculum. The purpose of this study was to investigate undergraduate students' perception of two different simulation methods for practicing clinical reasoning skills and technical skills in oral and maxillofacial surgery. Forty-seven students participating in the oral and maxillofacial surgery course at Karolinska Institutet during their final year were included. Three different oral surgery patient cases were created in a Virtual Patient (VP) Simulation system (Web-SP) and used for training clinical reasoning. A mandibular third molar surgery simulator with tactile feedback, providing hands on training in the bone removal and tooth sectioning in third molar surgery, was also tested. A seminar was performed using the combination of these two simulators where students' perception of the two different simulation methods was assessed by means of a questionnaire. The response rate was 91.5% (43/47). The students were positive to the VP cases, although they rated their possible improvement of clinical reasoning skills as moderate. The students' perception of improved technical skills after training in the mandibular third molar surgery simulator was rated high. The majority of the students agreed that both simulation techniques should be included in the curriculum and strongly agreed that it was a good idea to use the two simulators in concert. The importance of feedback from the senior experts during simulator training was emphasised. The two tested simulation methods were well accepted and most students agreed that the future curriculum would benefit from permanent inclusion of these exercises, especially when used in combination. The results also stress the importance of teaching technical skills and clinical reasoning in concert.

Late Complications of Chest Wall Reconstruction: Management of Painful Sternal Nonunion

PubMed Central

Chepla, Kyle J.; Salgado, Christopher J.; Tang, Cathy J.; Mardini, Samir; Evans, Karen K.

2011-01-01

Although rare, sternal nonunion after median sternotomy or traumatic injury is associated with a high rate of morbidity. Pain and sternal clicking are two of the most common complaints and reasons these patients seek evaluation and treatment. Diagnosis of sternal nonunion is based on a thorough history and physical examination and can be confirmed with subsequent radiographic imaging. The treatment for symptomatic sternal nonunion requires stable fixation of the bony fragments and chest wall after the debridement of all nonviable bony and soft tissue by the cardiothoracic or reconstructive surgery team. Multiple fixation techniques have been described and incorporate a wide variety of materials including combinations of wires, cables, pins, bands, staples, and plates. Most recently, several new commercially available plating systems have demonstrated low recurrence and complication rates and resolution of the patient's symptoms on follow-up evaluation. Included in this review are three cases demonstrating the management of symptomatic sternal nonunion using these new techniques and review the history, diagnosis, risk factor, and classification, as well as several of the previously described fixation methods. PMID:22294948

Sparse approximation problem: how rapid simulated annealing succeeds and fails

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Kabashima, Yoshiyuki

2016-03-01

Information processing techniques based on sparseness have been actively studied in several disciplines. Among them, a mathematical framework to approximately express a given dataset by a combination of a small number of basis vectors of an overcomplete basis is termed the sparse approximation. In this paper, we apply simulated annealing, a metaheuristic algorithm for general optimization problems, to sparse approximation in the situation where the given data have a planted sparse representation and noise is present. The result in the noiseless case shows that our simulated annealing works well in a reasonable parameter region: the planted solution is found fairly rapidly. This is true even in the case where a common relaxation of the sparse approximation problem, the G-relaxation, is ineffective. On the other hand, when the dimensionality of the data is close to the number of non-zero components, another metastable state emerges, and our algorithm fails to find the planted solution. This phenomenon is associated with a first-order phase transition. In the case of very strong noise, it is no longer meaningful to search for the planted solution. In this situation, our algorithm determines a solution with close-to-minimum distortion fairly quickly.

Using elements of hypnosis prior to or during pediatric dental treatment.

PubMed

Peretz, Benjamin; Bercovich, Roly; Blumer, Sigalit

2013-01-01

Most dental practitioners are familiar with pediatric patients expressing dental fear or anxiety. Occasionally, the dentist may encounter a situation where all behavioral techniques fail, while, for some reason, premedication or general anesthesia are contraindicated or rejected by the patient or his/her parents and a different approach is required. Hypnosis may solve the problem in some cases. The purpose of this study was to review the literature about techniques that use elements of hypnosis and hypnotic techniques prior to or during pediatric dental treatment. There is a limited amount of literature regarding the use of hypnosis and hypnotic elements in pediatric dentistry. Induction techniques, reframing, distraction, imagery suggestions, and hypnosis are identified, although mostly anecdotally, while there are very few structured controlled studies. Nevertheless, the advantages of using hypnotic elements and hypnosis in pediatric dentistry are evident.

Rubber dam isolation--key to success in diastema closure technique with direct composite resin.

PubMed

Barros de Campos, Paulo Ricardo; Maia, Rodrigo Rocha; Rodrigues de Menezes, Livia; Barbosa, Isabel Ferreira; Carneiro da Cunha, Amanda; da Silveira Pereira, Gisele Damiana

2015-01-01

The use of direct composite resin for diastema closure has technique advantages, including that the restorative procedure can be carried out in one appointment at a reasonable cost and without the removal of sound tooth structure. The use of a rubber dam for closing diastemas with composite resin is of paramount importance as it prevents moisture contamination and ensures increased gingival retraction compared to other techniques. This provides better access to the cervical area of the tooth, facilitating proper placement of resin to recreate the natural anatomical contours and contact point. Thus, there is a more natural adaptation of the restoration to the gingival tissue, avoiding a space between the papilla and the restored tooth. To illustrate the advantages of this technique, two diastema closure cases are presented using direct composite resin with rubber dam isolation.

Combining bimodal presentation schemes and buzz groups improves clinical reasoning and learning at morning report.

PubMed

Balslev, Thomas; Rasmussen, Astrid Bruun; Skajaa, Torjus; Nielsen, Jens Peter; Muijtjens, Arno; De Grave, Willem; Van Merriënboer, Jeroen

2014-12-11

Abstract Morning reports offer opportunities for intensive work-based learning. In this controlled study, we measured learning processes and outcomes with the report of paediatric emergency room patients. Twelve specialists and 12 residents were randomised into four groups and discussed the same two paediatric cases. The groups differed in their presentation modality (verbal only vs. verbal + text) and the use of buzz groups (with vs. without). The verbal interactions were analysed for clinical reasoning processes. Perceptions of learning and judgment of learning were reported in a questionnaire. Diagnostic accuracy was assessed by a 20-item multiple-choice test. Combined bimodal presentation and buzz groups increased the odds ratio of clinical reasoning to occur in the discussion of cases by a factor of 1.90 (p = 0.013), indicating superior reasoning for buzz groups working with bimodal materials. For specialists, a positive effect of bimodal presentation was found on perceptions of learning (p < 0.05), and for residents, a positive effect of buzz groups was found on judgment of learning (p < 0.005). A positive effect of bimodal presentation on diagnostic accuracy was noted in the specialists (p < 0.05). Combined bimodal presentation and buzz group discussion of emergency cases improves clinicians' clinical reasoning and learning.

Application of gas chromatography to analysis of spirit-based alcoholic beverages.

PubMed

Wiśniewska, Paulina; Śliwińska, Magdalena; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek

2015-01-01

Spirit-based beverages are alcoholic drinks; their production processes are dependent on the type and origin of raw materials. The composition of this complex matrix is difficult to analyze, and scientists commonly choose gas chromatography techniques for this reason. With a wide selection of extraction methods and detectors it is possible to provide qualitative and quantitative analysis for many chemical compounds with various functional groups. This article describes different types of gas chromatography techniques and their most commonly used associated extraction techniques (e.g., LLE, SPME, SPE, SFE, and SBME) and detectors (MS, TOFMS, FID, ECD, NPD, AED, O or EPD). Additionally, brief characteristics of internationally popular spirit-based beverages and application of gas chromatography to the analysis of selected alcoholic drinks are presented.

Slow Crack Growth of Brittle Materials With Exponential Crack-Velocity Formulation. Part 2; Constant Stress Rate Experiments

NASA Technical Reports Server (NTRS)

Choi, Sung R.; Nemeth, Noel N.; Gyekenyesi, John P.

2002-01-01

The previously determined life prediction analysis based on an exponential crack-velocity formulation was examined using a variety of experimental data on glass and advanced structural ceramics in constant stress rate and preload testing at ambient and elevated temperatures. The data fit to the relation of strength versus the log of the stress rate was very reasonable for most of the materials. Also, the preloading technique was determined equally applicable to the case of slow-crack-growth (SCG) parameter n greater than 30 for both the power-law and exponential formulations. The major limitation in the exponential crack-velocity formulation, however, was that the inert strength of a material must be known a priori to evaluate the important SCG parameter n, a significant drawback as compared with the conventional power-law crack-velocity formulation.

River embankment characterization: The joint use of geophysical and geotechnical techniques

NASA Astrophysics Data System (ADS)

Perri, Maria Teresa; Boaga, Jacopo; Bersan, Silvia; Cassiani, Giorgio; Cola, Simonetta; Deiana, Rita; Simonini, Paolo; Patti, Salvatore

2014-11-01

Recent flood events in Northern Italy (particularly in the Veneto Region) have brought river embankments into the focus of public attention. Many of these embankments are more than 100 years old and have been repeatedly repaired, so that detailed information on their current structure is generally missing. The monitoring of these structures is currently based, for the most part, on visual inspection and localized measurements of the embankment material parameters. However, this monitoring is generally insufficient to ensure an adequate safety level against floods. For these reasons there is an increasing demand for fast and accurate investigation methods, such as geophysical techniques. These techniques can provide detailed information on the subsurface structures, are non-invasive, cost-effective, and faster than traditional methods. However, they need verification in order to provide reliable results, particularly in complex and reworked man-made structures such as embankments. In this paper we present a case study in which three different geophysical techniques have been applied: electrical resistivity tomography (ERT), frequency domain electromagnetic induction (FDEM) and Ground Penetrating Radar (GPR). Two test sites have been selected, both located in the Province of Venice (NE Italy) where the Tagliamento River has large embankments. The results obtained with these techniques have been calibrated against evidence resolving from geotechnical investigations. The pros and cons of each technique, as well as their relative merit at identifying the specific features of the embankments in this area, are highlighted. The results demonstrate that geophysical techniques can provide very valuable information for embankment characterization, provided that the data interpretation is constrained via direct evidence, albeit limited in space.

A formative evaluation of problem-based learning as an instructional strategy in a medical laboratory technician course

NASA Astrophysics Data System (ADS)

Nelson, Diane Patricia

2002-09-01

This study is a formative evaluation of problem-based learning as an effective course delivery strategy in a second year introductory Medical Laboratory Technician discipline-specific hematology course. This strategy can serve two purposes in this type of course: discipline specific content knowledge and process skills learning. A needs study identified that students required additional workplace skills as they entered the clinical internship. Students tested well on the national registry examinations, discipline-specific content knowledge, but group process skills needed improvement in the areas of collaboration, communication, and critical reasoning. Problem-based learning was identified as an change intervention to help provide these skills. A search of the literature revealed that the Baker College cultural and physical environment would support this intervention. Twelve cases were written, situated in a clinical laboratory environment, addressing learning issues identified in a modified Delphi survey of laboratory personnel e.g. fiscal responsibility, turn-around time, invasiveness of laboratory techniques, and holistic view of healthcare environment. A hematology class of 13 students received the intervention. The cases were structured to proceed from instructor-centered (guided) learning issues to learner-centered learning issues. Observations of the in-group collaboration processes were documented, as well as oral presentations and critical reasoning, with students given periodic feedback on these skills. Student surveys provided data about satisfaction, attitude to PBL process, and self-efficacy. Multiple choice discipline-specific content examinations were given and compared with classes from the previous four years. The study found that students receiving the PBL treatment scored as well as or better than students from previous years on traditional multiple choice exams. Recall questions showed positive significance and application/analysis questions showed no significance from previous years. Clinical correlations end-of-case evaluations addressing the issues of thoroughness of investigation, supporting evidence, accuracy of information, order and clarity of thought showed positive improvement across the intervention, as did the PBL processes of in-group collaboration skills, teamwork skills, and presentation skills. By the end of the intervention, students expressed preference for student-centered learning issues.

Management of the aging nose.

PubMed

Quatela, Vito C; Pearson, James M

2009-11-01

As a growing segment of our population, mature patients seeking rhinoplasty for both functional and aesthetic reasons will increasingly be encountered by the facial plastic surgeon. The aging process is characterized by a gradual derotation and deprojection of the nasal tip. This article provides an overview of versatile and proven techniques that may be applied to the majority of aging nose rhinoplasty cases and that have been found to yield predictable and lasting results. Copyright Thieme Medical Publishers.

NMR-based urine analysis in rats: prediction of proximal tubule kidney toxicity and phospholipidosis.

PubMed

Lienemann, Kai; Plötz, Thomas; Pestel, Sabine

2008-01-01

The aim of safety pharmacology is early detection of compound-induced side-effects. NMR-based urine analysis followed by multivariate data analysis (metabonomics) identifies efficiently differences between toxic and non-toxic compounds; but in most cases multiple administrations of the test compound are necessary. We tested the feasibility of detecting proximal tubule kidney toxicity and phospholipidosis with metabonomics techniques after single compound administration as an early safety pharmacology approach. Rats were treated orally, intravenously, inhalatively or intraperitoneally with different test compounds. Urine was collected at 0-8 h and 8-24 h after compound administration, and (1)H NMR-patterns were recorded from the samples. Variation of post-processing and feature extraction methods led to different views on the data. Support Vector Machines were trained on these different data sets and then aggregated as experts in an Ensemble. Finally, validity was monitored with a cross-validation study using a training, validation, and test data set. Proximal tubule kidney toxicity could be predicted with reasonable total classification accuracy (85%), specificity (88%) and sensitivity (78%). In comparison to alternative histological studies, results were obtained quicker, compound need was reduced, and very importantly fewer animals were needed. In contrast, the induction of phospholipidosis by the test compounds could not be predicted using NMR-based urine analysis or the previously published biomarker PAG. NMR-based urine analysis was shown to effectively predict proximal tubule kidney toxicity after single compound administration in rats. Thus, this experimental design allows early detection of toxicity risks with relatively low amounts of compound in a reasonably short period of time.

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

Bovine Acellular Dermal Matrix for Levator Lengthening in Thyroid-Related Upper-Eyelid Retraction.

PubMed

Sun, Jing; Liu, Xingtong; Zhang, Yidan; Huang, Yazhuo; Zhong, Sisi; Fang, Sijie; Zhuang, Ai; Li, Yinwei; Zhou, Huifang; Fan, Xianqun

2018-05-02

BACKGROUND Eyelid retraction is the most common and often the first sign of thyroid eye disease (TED). Upper-eyelid retraction causes both functional and cosmetic problems. In order to correct the position of the upper eyelid, surgery is required. Many procedures have demonstrated good outcomes in mild and moderate cases; however, unpredictable results have been obtained in severe cases. Dryden introduced an upper-eyelid-lengthening procedure, which used scleral grafts, but outcomes were unsatisfactory. A new technique is introduced in this study as a reasonable alternative for TED-related severe upper-eyelid retraction correction. MATERIAL AND METHODS An innovative technique for levator lengthening using bovine acellular dermal matrix as a spacer graft is introduced for severe upper-eyelid retraction secondary to TED. Additionally, 2 modifications were introduced: the fibrous cords scattered on the surface of the levator aponeurosis were excised and the orbital fat pad anterior to the aponeurosis was dissected and sutured into the skin closure in a "skin-tarsus-fat-skin" fashion. RESULTS The modified levator-lengthening surgery was performed on 32 eyelids in 26 patients consisting of 21 women and 5 men (mean age, 37.8 years; age range, 19-67 years). After corrective surgery, the average upper margin reflex distance was lowered from 7.7±0.85 mm to 3.3±0.43 mm. Eighteen cases (69%) had perfect results, while 6 cases (23%) had acceptable results. CONCLUSIONS A modified levator-lengthening procedure using bovine acellular dermal matrix as a spacer graft ameliorated both the symptoms and signs of severe upper-eyelid retraction secondary to TED. This procedure is a reasonable alternative for correction of TED-related severe upper-eyelid retraction.

Bovine Acellular Dermal Matrix for Levator Lengthening in Thyroid-Related Upper-Eyelid Retraction

PubMed Central

Sun, Jing; Liu, Xingtong; Zhang, Yidan; Huang, Yazhuo; Zhong, Sisi; Fang, Sijie; Zhuang, Ai; Li, Yinwei; Zhou, Huifang

2018-01-01

Background Eyelid retraction is the most common and often the first sign of thyroid eye disease (TED). Upper-eyelid retraction causes both functional and cosmetic problems. In order to correct the position of the upper eyelid, surgery is required. Many procedures have demonstrated good outcomes in mild and moderate cases; however, unpredictable results have been obtained in severe cases. Dryden introduced an upper-eyelid-lengthening procedure, which used scleral grafts, but outcomes were unsatisfactory. A new technique is introduced in this study as a reasonable alternative for TED-related severe upper-eyelid retraction correction. Material/Methods An innovative technique for levator lengthening using bovine acellular dermal matrix as a spacer graft is introduced for severe upper-eyelid retraction secondary to TED. Additionally, 2 modifications were introduced: the fibrous cords scattered on the surface of the levator aponeurosis were excised and the orbital fat pad anterior to the aponeurosis was dissected and sutured into the skin closure in a “skin-tarsus-fat-skin” fashion. Results The modified levator-lengthening surgery was performed on 32 eyelids in 26 patients consisting of 21 women and 5 men (mean age, 37.8 years; age range, 19–67 years). After corrective surgery, the average upper margin reflex distance was lowered from 7.7±0.85 mm to 3.3±0.43 mm. Eighteen cases (69%) had perfect results, while 6 cases (23%) had acceptable results. Conclusions A modified levator-lengthening procedure using bovine acellular dermal matrix as a spacer graft ameliorated both the symptoms and signs of severe upper-eyelid retraction secondary to TED. This procedure is a reasonable alternative for correction of TED-related severe upper-eyelid retraction. PMID:29718902

Plausible inference: A multi-valued logic for problem solving

NASA Technical Reports Server (NTRS)

Friedman, L.

1979-01-01

A new logic is developed which permits continuously variable strength of belief in the truth of assertions. Four inference rules result, with formal logic as a limiting case. Quantification of belief is defined. Propagation of belief to linked assertions results from dependency-based techniques of truth maintenance so that local consistency is achieved or contradiction discovered in problem solving. Rules for combining, confirming, or disconfirming beliefs are given, and several heuristics are suggested that apply to revising already formed beliefs in the light of new evidence. The strength of belief that results in such revisions based on conflicting evidence are a highly subjective phenomenon. Certain quantification rules appear to reflect an orderliness in the subjectivity. Several examples of reasoning by plausible inference are given, including a legal example and one from robot learning. Propagation of belief takes place in directions forbidden in formal logic and this results in conclusions becoming possible for a given set of assertions that are not reachable by formal logic.

Technological innovations in the development of cardiovascular clinical information systems.

PubMed

Hsieh, Nan-Chen; Chang, Chung-Yi; Lee, Kuo-Chen; Chen, Jeen-Chen; Chan, Chien-Hui

2012-04-01

Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.

Dengue transmission based on urban environmental gradients in different cities of Pakistan.

PubMed

Khalid, Bushra; Ghaffar, Abdul

2015-03-01

This study focuses on the dengue transmission in different regions of Pakistan. For this purpose, the data of dengue cases for 2009-2012 from four different cities (Rawalpindi, Islamabad, Lahore, and Karachi) of the country is collected, evaluated, and compiled. To identify the reasons and regions of higher risk of Dengue transmission, land use classification, analysis of climate covariates and drainage patterns was done. Analysis involves processing of SPOT 5 10 m, Landsat TM 30 m data sets, and SRTM 90 m digital elevation models by using remote sensing and GIS techniques. The results are based on the change in urbanization and population density, analysis of temperature, rainfall, and wind speed; calculation of drainage patterns including stream features, flow accumulation, and drainage density of the study areas. Results suggest that the low elevation areas with calm winds and minimum temperatures higher than the normal, rapid increase in unplanned urbanization, low flow accumulation, and higher drainage density areas favor the dengue transmission.

An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty

PubMed Central

Langlotz, Curtis P.; Shortliffe, Edward H.

1988-01-01

Decision theory and logical reasoning are both methods for representing and solving medical decision problems. We analyze the usefulness of these two approaches to medical therapy planning by establishing a simple correspondence between decision theory and non-monotonic logic, a formalization of categorical logical reasoning. The analysis indicates that categorical approaches to planning can be viewed as comprising two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of desirability of planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of categorical (nonmonotonic) reasoning: (1) Decision theory and artificial intelligence techniques are intended to solve different components of the planning problem. (2) When considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical logical reasoning for planning under certainty. (3) Because certain nonmonotonic programming paradigms (e.g., frame-based inheritance, rule-based planning, protocol-based reminders) are inherently problem-specific, they may be inappropriate to employ in the solution of certain types of planning problems. We discuss how these conclusions affect several current medical informatics research issues, including the construction of “very large” medical knowledge bases.

Revision Stapedectomy with Necrosis of the Long Process of the Incus: Does the Degree of Necrosis Matter? A Retrospective Clinical Study.

PubMed

Ghonim, Mohamed; Shabana, Yousef; Ashraf, Bassem; Salem, Mohamed

2017-04-01

To discuss the different modalities for managing necrosis of the long process of the incus in revision stapedectomy on the basis of the degree of necrosis and compare the results with those reported in the literature. Thirty-six patients underwent revision stapedectomy with the necrosis of the long process of the incus from 2009 to 2016. The patients were divided into three groups on the basis of the degree of necrosis. For group A (minimal necrosis), augmentation technique with bone cement was performed. For group B (partial necrosis), the cement plug technique was performed. For group C (sever necrosis), malleus relocation with malleovestibulopexy was performed using reshaped necrosed incus. Air and bone conduction thresholds at frequencies of 500-3000 Hz were reviewed pre- and postoperatively using conventional audiometry. The air-bone gap (ABG) and bone conduction thresholds were measured. Postoperative ABG was reduced to <10 dB in 28 cases (77.8%) and <20 dB in all cases (100%). There was no significant change in postoperative bone conduction thresholds. The mean patient follow-up duration was 23 (range, 18-36) months. The cement plug technique was used in 75% of cases. Managing necrosis of the long process of the incus in revision stapedectomy should be considered according to the degree of necrosis. The cement plug technique is considered to be a reasonable option in most cases. Malleus relocation with malleovestibulopexy is an effective alternative to prosthesis.

26 CFR 1.924(a)-1T - Temporary regulations; definition of foreign trading gross receipts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... related services furnished by the FSC (as described in this paragraph (d)(2)). In the case of a sale... the sale. In the case of a lease, reasonable expectations at the time of the lease are based on the... determined under the facts and circumstances of each case without regard to whether— (A) The services are...

A preliminary structural analysis of space-base living quarters modules to verify a weight-estimating technique

NASA Technical Reports Server (NTRS)

Grissom, D. S.; Schneider, W. C.

1971-01-01

The determination of a base line (minimum weight) design for the primary structure of the living quarters modules in an earth-orbiting space base was investigated. Although the design is preliminary in nature, the supporting analysis is sufficiently thorough to provide a reasonably accurate weight estimate of the major components that are considered to comprise the structural weight of the space base.

Cognitive problem solving patterns of medical students correlate with success in diagnostic case solutions.

PubMed

Kiesewetter, Jan; Ebersbach, René; Görlitz, Anja; Holzer, Matthias; Fischer, Martin R; Schmidmaier, Ralf

2013-01-01

Problem-solving in terms of clinical reasoning is regarded as a key competence of medical doctors. Little is known about the general cognitive actions underlying the strategies of problem-solving among medical students. In this study, a theory-based model was used and adapted in order to investigate the cognitive actions in which medical students are engaged when dealing with a case and how patterns of these actions are related to the correct solution. Twenty-three medical students worked on three cases on clinical nephrology using the think-aloud method. The transcribed recordings were coded using a theory-based model consisting of eight different cognitive actions. The coded data was analysed using time sequences in a graphical representation software. Furthermore the relationship between the coded data and accuracy of diagnosis was investigated with inferential statistical methods. The observation of all main actions in a case elaboration, including evaluation, representation and integration, was considered a complete model and was found in the majority of cases (56%). This pattern significantly related to the accuracy of the case solution (φ = 0.55; p<.001). Extent of prior knowledge was neither related to the complete model nor to the correct solution. The proposed model is suitable to empirically verify the cognitive actions of problem-solving of medical students. The cognitive actions evaluation, representation and integration are crucial for the complete model and therefore for the accuracy of the solution. The educational implication which may be drawn from this study is to foster students reasoning by focusing on higher level reasoning.

Constraint-based Temporal Reasoning with Preferences

NASA Technical Reports Server (NTRS)

Khatib, Lina; Morris, Paul; Morris, Robert; Rossi, Francesca; Sperduti, Alessandro; Venable, K. Brent

2005-01-01

Often we need to work in scenarios where events happen over time and preferences are associated to event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems require exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solvable. In this paper we identify one of such subclasses giving tractability results. Moreover, we describe two solvers for this class of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and robustness. Sometimes, however, temporal local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preferences, we show that machine learning techniques can be useful in this respect. In particular, we present a learning module based on a gradient descent technique which induces local temporal preferences from global ones. We also show the behavior of the learning module on randomly-generated examples.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision.

PubMed

Sgaier, Sema K; Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-09-13

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15-29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision

PubMed Central

Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-01-01

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15–29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior. PMID:28901285

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salloum, Maher; Fabian, Nathan D.; Hensinger, David M.

Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate itsmore » usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Finally, our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.« less

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

NASA Technical Reports Server (NTRS)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Space station advanced automation

NASA Technical Reports Server (NTRS)

Woods, Donald

1990-01-01

In the development of a safe, productive and maintainable space station, Automation and Robotics (A and R) has been identified as an enabling technology which will allow efficient operation at a reasonable cost. The Space Station Freedom's (SSF) systems are very complex, and interdependent. The usage of Advanced Automation (AA) will help restructure, and integrate system status so that station and ground personnel can operate more efficiently. To use AA technology for the augmentation of system management functions requires a development model which consists of well defined phases of: evaluation, development, integration, and maintenance. The evaluation phase will consider system management functions against traditional solutions, implementation techniques and requirements; the end result of this phase should be a well developed concept along with a feasibility analysis. In the development phase the AA system will be developed in accordance with a traditional Life Cycle Model (LCM) modified for Knowledge Based System (KBS) applications. A way by which both knowledge bases and reasoning techniques can be reused to control costs is explained. During the integration phase the KBS software must be integrated with conventional software, and verified and validated. The Verification and Validation (V and V) techniques applicable to these KBS are based on the ideas of consistency, minimal competency, and graph theory. The maintenance phase will be aided by having well designed and documented KBS software.

Non-Standard Forms of Human Residence - The Past and the Future

NASA Astrophysics Data System (ADS)

Wojtkun, Grzegorz

2017-10-01

Since the dawn a man has been taking numerous settlement actions in places even useless for this purpose, for example in areas water- or permafrost-stricken. A perfect example of this in European conditions have become households built in Friesland, on the Scandinavian Peninsula (Lapland) and in the western part of Jutland Peninsula. The scale of the building development, created within it neighbourly relations, as well as used on that occasion materials, techniques and technologies seem to be particularly interesting in the case of so-called negative evolution of the human environment and the disappearance of active-citizen attitudes. For these reasons, research undertakes aiming to assess the usefulness of construction and settlement solutions in the past should be regarded as reasonable.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

NASA Astrophysics Data System (ADS)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

Scientific Reasoning and Its Relationship with Problem Solving: The Case of Upper Primary Science Teachers

ERIC Educational Resources Information Center

Alshamali, Mahmoud A.; Daher, Wajeeh M.

2016-01-01

This study aimed at identifying the levels of scientific reasoning of upper primary stage (grades 4-7) science teachers based on their use of a problem-solving strategy. The study sample (N = 138; 32 % male and 68 % female) was randomly selected using stratified sampling from an original population of 437 upper primary school teachers. The…

Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks.

PubMed

Douali, Nassim; Csaba, Huszka; De Roo, Jos; Papageorgiou, Elpiniki I; Jaulent, Marie-Christine

2014-01-01

Several studies have described the prevalence and severity of diagnostic errors. Diagnostic errors can arise from cognitive, training, educational and other issues. Examples of cognitive issues include flawed reasoning, incomplete knowledge, faulty information gathering or interpretation, and inappropriate use of decision-making heuristics. We describe a new approach, case-based fuzzy cognitive maps, for medical diagnosis and evaluate it by comparison with Bayesian belief networks. We created a semantic web framework that supports the two reasoning methods. We used database of 174 anonymous patients from several European hospitals: 80 of the patients were female and 94 male with an average age 45±16 (average±stdev). Thirty of the 80 female patients were pregnant. For each patient, signs/symptoms/observables/age/sex were taken into account by the system. We used a statistical approach to compare the two methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The Geomatics Contribution for the Valorisation Project in the Rocca of San Silvestro Landscape Site

NASA Astrophysics Data System (ADS)

Brocchini, D.; Chiabrando, F.; Colucci, E.; Sammartano, G.; Spanò, A.; Teppati Losè, L.; Villa, A.

2017-05-01

This paper proposes an emblematic project where several multi-sensor strategies for spatial data acquisition and management, range based and image based, were combined to create a series of integrated territorial and architectural scale products characterized by a rich multi-content nature. The work presented here was finalized in a test site that is composed by an ensemble of diversified cultural deposits; the objects that were surveyed and modelled range from the landscape with its widespread mining sites, the main tower with its defensive role, the urban configuration of the settlement, the building systems and techniques, a medieval mine. For this reason, the Rocca of San Silvestro represented a perfect test case, due to its complex and multi-stratified character. This archaeological site is a medieval fortified village near the municipality of Campiglia Marittima (LI), Italy. The Rocca is part of an Archaeological Mines Park and is included in the Parchi della Val di Cornia (a system of archaeological parks, natural parks and museums in the south-west of Tuscany). The fundamental role of a deep knowledge about a cultural artefact before the planning of a restoration and valorisation project is globally recognized; the qualitative and quantitative knowledge provided by geomatics techniques is part of this process. The paper will present the different techniques that were used, the products that were obtained and will focus on some mapping and WEB GIS applications and analyses that were performed and considerations that were made.

Women's reasons for choosing abortion method: A systematic literature review.

PubMed

Kanstrup, Charlotte; Mäkelä, Marjukka; Hauskov Graungaard, Anette

2017-07-01

We aim to describe and classify reasons behind women's choice between medical and surgical abortion. A systematic literature review was conducted in PubMed and PsycINFO in October 2015. The subjects were women in early pregnancy opting for abortion at clinics or hospitals in high-income countries. We extracted women's reasons for choice of abortion method and analysed these qualitatively, looking at main reasons for choosing either medical or surgical abortion. Reasons for choice of method were classified to five main groups: technical nature of the intervention, fear of complications, fear of surgery or anaesthesia, timing and sedation. Reasons for selecting medical abortion were often based on the perception of the method being 'more natural' and the wish to have abortion in one's home in addition to fear of complications. Women who opted for surgical abortion appreciated the quicker process, viewed it as the safer option, and wished to avoid pain and excess bleeding. Reasons were often based on emotional reactions, previous experiences and a lack of knowledge about the procedures. Some topics such as pain or excess bleeding received little attention. Overall the quality of the studies was low, most studies were published more than 10 years ago, and the generalisability of the findings was poor. Women did not base their choice of abortion method only on rational information from professionals but also on emotions and especially fears. Support techniques for a more informed choice are needed. Recent high-quality studies in this area are lacking.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

PubMed

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

PubMed Central

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896

Autonomous Distributed Congestion Control Scheme in WCDMA Network

NASA Astrophysics Data System (ADS)

Ahmad, Hafiz Farooq; Suguri, Hiroki; Choudhary, Muhammad Qaisar; Hassan, Ammar; Liaqat, Ali; Khan, Muhammad Umer

Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.

Evicase: an evidence-based case structuring approach for personalized healthcare.

PubMed

Carmeli, Boaz; Casali, Paolo; Goldbraich, Anna; Goldsteen, Abigail; Kent, Carmel; Licitra, Lisa; Locatelli, Paolo; Restifo, Nicola; Rinott, Ruty; Sini, Elena; Torresani, Michele; Waks, Zeev

2012-01-01

The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside. It then uses machine learning algorithms to produce statistical results and aggregators, weighted predictions, and appropriate recommendations. Designed as a stand-alone structure, Evicase can be used for a range of decision support applications including guideline adherence monitoring and personalized prognostic predictions.

Supporting Preservice Teacher Inquiry with Electronic Portfolios

ERIC Educational Resources Information Center

Shepherd, Craig; Hannafin, Michael

2011-01-01

Six preservice social studies teachers created electronic portfolios to examine techniques believed to promote active student engagement during a 12-week field experience. Inquiry into these practices was facilitated through embedded tutorials, assignment suggestions, and question prompts based on principles of evidential reasoning. Although…

An efficient numerical method for solving the Boltzmann equation in multidimensions

NASA Astrophysics Data System (ADS)

Dimarco, Giacomo; Loubère, Raphaël; Narski, Jacek; Rey, Thomas

2018-01-01

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) (Dimarco and Loubère, 2013 [26]) originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme combines a robust and fast method for treating the transport part based on an innovative Lagrangian technique supplemented with conservative fast spectral schemes to treat the collisional operator by means of an operator splitting approach. This approach along with several implementation features related to the parallelization of the algorithm permits to construct an efficient simulation tool which is numerically tested against exact and reference solutions on classical problems arising in rarefied gas dynamic. We present results up to the 3 D × 3 D case for unsteady flows for the Variable Hard Sphere model which may serve as benchmark for future comparisons between different numerical methods for solving the multidimensional Boltzmann equation. For this reason, we also provide for each problem studied details on the computational cost and memory consumption as well as comparisons with the BGK model or the limit model of compressible Euler equations.

Bridge scour monitoring methods at three sites in Wisconsin

USGS Publications Warehouse

Walker, John F.; Hughes, Peter E.

2005-01-01

Of the nearly 11,500 bridges in Wisconsin, 89 have been assessed with critical scour conditions. The U.S. Geological Survey, in cooperation with the Wisconsin Department of Transportation, the Marathon County Highway Department, and the Jefferson County Highway Department, performed routine monitoring of streambed elevations for three bridges. Two monitoring approaches were employed: (1) manual monitoring using moderately simple equipment, and (2) automated monitoring, using moderately sophisticated electronic equipment. The results from all three sites demonstrate that both techniques can produce reasonable measurements of streambed elevation. The manual technique has a lower annual operating cost, and is useful for cases where documentation of long-term trends is desired. The automated technique has a higher annual operating cost and is useful for real-time monitoring of episodic events with short time durations. 

Comparison of anatomy-based, fluence-based and aperture-based treatment planning approaches for VMAT

NASA Astrophysics Data System (ADS)

Rao, Min; Cao, Daliang; Chen, Fan; Ye, Jinsong; Mehta, Vivek; Wong, Tony; Shepard, David

2010-11-01

Volumetric modulated arc therapy (VMAT) has the potential to reduce treatment times while producing comparable or improved dose distributions relative to fixed-field intensity-modulated radiation therapy. In order to take full advantage of the VMAT delivery technique, one must select a robust inverse planning tool. The purpose of this study was to evaluate the effectiveness and efficiency of VMAT planning techniques of three categories: anatomy-based, fluence-based and aperture-based inverse planning. We have compared these techniques in terms of the plan quality, planning efficiency and delivery efficiency. Fourteen patients were selected for this study including six head-and-neck (HN) cases, and two cases each of prostate, pancreas, lung and partial brain. For each case, three VMAT plans were created. The first VMAT plan was generated based on the anatomical geometry. In the Elekta ERGO++ treatment planning system (TPS), segments were generated based on the beam's eye view (BEV) of the target and the organs at risk. The segment shapes were then exported to Pinnacle3 TPS followed by segment weight optimization and final dose calculation. The second VMAT plan was generated by converting optimized fluence maps (calculated by the Pinnacle3 TPS) into deliverable arcs using an in-house arc sequencer. The third VMAT plan was generated using the Pinnacle3 SmartArc IMRT module which is an aperture-based optimization method. All VMAT plans were delivered using an Elekta Synergy linear accelerator and the plan comparisons were made in terms of plan quality and delivery efficiency. The results show that for cases of little or modest complexity such as prostate, pancreas, lung and brain, the anatomy-based approach provides similar target coverage and critical structure sparing, but less conformal dose distributions as compared to the other two approaches. For more complex HN cases, the anatomy-based approach is not able to provide clinically acceptable VMAT plans while highly conformal dose distributions were obtained using both aperture-based and fluence-based inverse planning techniques. The aperture-based approach provides improved dose conformity than the fluence-based technique in complex cases.

XRF analysis to identify historical photographic processes: The case of some Interguglielmi Jr.'s images from the Palermo Municipal Archive

NASA Astrophysics Data System (ADS)

Modica, A.; Alberghina, M. F.; Brai, M.; Bruno, M.; Di Bella, M.; Fontana, D.; Tranchina, L.

2017-06-01

In the early period, even though professional photographers worked with similar techniques and products, their artistic and commercial aims determined different choices and led them to follow different, often personal, recipes. For this reason, identification of the techniques through date and name of the photographer or through some visual features like colour, tonality and surface of the image layer, often needs further investigation to be proved. Chemical characterization, carried out in a non or micro destructive way, can be crucial to provide useful information about the original composition, degradation process, realization technique, in obtaining an indirect dating of the photograph and/or to choose the most correct conservation treatment. In our case, x-ray fluorescence (XRF) analysis was used to confirm the chemical composition of eleven historical photographs dated between the end of the 19th century and the beginning of the 20th, shot in Palermo (Sicily) by a renowned photographer of the time, and pasted on their original cardboards. The elemental identification, obtained with a non destructive approach, provided important information to distinguish among different photographic techniques in terms of distribution and characterization of chemical elements markers in the photographic surface.

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

NASA Technical Reports Server (NTRS)

Iverson, David L.

2005-01-01

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Gradient titanium and silver based carbon coatings deposited on AISI316L

NASA Astrophysics Data System (ADS)

Batory, Damian; Reczulska, Malgorzata Czerniak-; Kolodziejczyk, Lukasz; Szymanski, Witold

2013-06-01

The constantly growing market for medical implants and devices caused mainly due to a lack of proper attention attached to the physical condition as well as extreme sports and increased elderly population creates the need of new biocompatible biomaterials with controlled bioactivity and certain useful properties. According to many literature reports, regarding the modifications of variety of different biomaterials using the surface engineering techniques and their biological and physicochemical examination results, the most promising material for great spectra of medical applications seem to be carbon layers. Another issue is the interaction between the implant material and surrounding tissue. In particular cases this interface area is directly exposed to air. Abovementioned concern occurs mainly in case of the external fixations, thus they are more vulnerable to infection. Therefore a crucial role has the inhibition of bacterial adhesion that may prevent implant-associated infections, occurrence of other numerous complications and in particular cases rejection of the implant. For this reason additional features of carbon coatings like antibacterial properties seem to be desired and justified. Silver doped diamond-like carbon coatings with different Ag concentrations were prepared by hybrid RF PACVD/MS (Radio Frequency Plasma Assisted Chemical Vapor Deposition/Magnetron Sputtering) deposition technique. Physicochemical parameters like chemical composition, morphology and surface topography, hardness and adhesion were determined. Examined layers showed a uniform distribution of silver in the amorphous DLC matrix, high value of H/E ratio, good adhesion and beneficial topography which make them a perfect material for medical applications e.g. modification of implants for the external fixations.

Clinical reasoning and population health: decision making for an emerging paradigm of health care.

PubMed

Edwards, Ian; Richardson, Barbara

2008-01-01

Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

Hybrid LES RANS technique based on a one-equation near-wall model

NASA Astrophysics Data System (ADS)

Breuer, M.; Jaffrézic, B.; Arora, K.

2008-05-01

In order to reduce the high computational effort of wall-resolved large-eddy simulations (LES), the present paper suggests a hybrid LES RANS approach which splits up the simulation into a near-wall RANS part and an outer LES part. Generally, RANS is adequate for attached boundary layers requiring reasonable CPU-time and memory, where LES can also be applied but demands extremely large resources. Contrarily, RANS often fails in flows with massive separation or large-scale vortical structures. Here, LES is without a doubt the best choice. The basic concept of hybrid methods is to combine the advantages of both approaches yielding a prediction method, which, on the one hand, assures reliable results for complex turbulent flows, including large-scale flow phenomena and massive separation, but, on the other hand, consumes much fewer resources than LES, especially for high Reynolds number flows encountered in technical applications. In the present study, a non-zonal hybrid technique is considered (according to the signification retained by the authors concerning the terms zonal and non-zonal), which leads to an approach where the suitable simulation technique is chosen more or less automatically. For this purpose the hybrid approach proposed relies on a unique modeling concept. In the LES mode a subgrid-scale model based on a one-equation model for the subgrid-scale turbulent kinetic energy is applied, where the length scale is defined by the filter width. For the viscosity-affected near-wall RANS mode the one-equation model proposed by Rodi et al. (J Fluids Eng 115:196 205, 1993) is used, which is based on the wall-normal velocity fluctuations as the velocity scale and algebraic relations for the length scales. Although the idea of combined LES RANS methods is not new, a variety of open questions still has to be answered. This includes, in particular, the demand for appropriate coupling techniques between LES and RANS, adaptive control mechanisms, and proper subgrid-scale and RANS models. Here, in addition to the study on the behavior of the suggested hybrid LES RANS approach, special emphasis is put on the investigation of suitable interface criteria and the adjustment of the RANS model. To investigate these issues, two different test cases are considered. Besides the standard plane channel flow test case, the flow over a periodic arrangement of hills is studied in detail. This test case includes a pressure-induced flow separation and subsequent reattachment. In comparison with a wall-resolved LES prediction encouraging results are achieved.

Plasmonic biosensors.

PubMed

Hill, Ryan T

2015-01-01

The unique optical properties of plasmon resonant nanostructures enable exploration of nanoscale environments using relatively simple optical characterization techniques. For this reason, the field of plasmonics continues to garner the attention of the biosensing community. Biosensors based on propagating surface plasmon resonances (SPRs) in films are the most well-recognized plasmonic biosensors, but there is great potential for the new, developing technologies to surpass the robustness and popularity of film-based SPR sensing. This review surveys the current plasmonic biosensor landscape with emphasis on the basic operating principles of each plasmonic sensing technique and the practical considerations when developing a sensing platform with the various techniques. The 'gold standard' film SPR technique is reviewed briefly, but special emphasis is devoted to the up-and-coming localized surface plasmon resonance and plasmonically coupled sensor technology. © 2014 Wiley Periodicals, Inc.

A Survey on Ambient Intelligence in Health Care

PubMed Central

Acampora, Giovanni; Cook, Diane J.; Rashidi, Parisa; Vasilakos, Athanasios V.

2013-01-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths. PMID:24431472

A Survey on Ambient Intelligence in Health Care.

PubMed

Acampora, Giovanni; Cook, Diane J; Rashidi, Parisa; Vasilakos, Athanasios V

2013-12-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

The business case for building better hospitals through evidence-based design.

PubMed

Sadler, Blair L; DuBose, Jennifer; Zimring, Craig

2008-01-01

After establishing the connection between building well-designed evidence-based facilities and improved safety and quality for patients, families, and staff, this article presents the compelling business case for doing so. It demonstrates why ongoing operating savings and initial capital costs must be analyzed and describes specific steps to ensure that design innovations are implemented effectively. Hospital leaders and boards are now beginning to face a new reality: They can no longer tolerate preventable hospital-acquired conditions such as infections, falls, and injuries to staff or unnecessary intra-hospital patient transfers that can increase errors. Nor can they subject patients and families to noisy, confusing environments that increase anxiety and stress. They must effectively deploy all reasonable quality improvement techniques available. To be optimally effective, a variety of tactics must be combined and implemented in an integrated way. Hospital leadership must understand the clear connection between building well-designed healing environments and improved healthcare safety and quality for patients, families, and staff, as well as the compelling business case for doing so. Emerging pay-for-performance (P4P) methodologies that reward hospitals for quality and refuse to pay hospitals for the harm they cause (e.g., infections and falls) further strengthen this business case. When planning to build a new hospital or to renovate an existing facility, healthcare leaders should address a key question: Will the proposed project incorporate all relevant and proven evidence-based design innovations to optimize patient safety, quality, and satisfaction as well as workforce safety, satisfaction, productivity, and energy efficiency? When conducting a business case analysis for a new project, hospital leaders should consider ongoing operating savings and the market share impact of evidence-based design interventions as well as initial capital costs. They should consider taking the 10 steps recommended to ensure an optimal, cost-effective hospital environment. A return-on-investment (ROI) framework is put forward for the use of individual organizations.

Differential Game Theory Application to Intelligent Missile Guidance

DTIC Science & Technology

2013-06-01

guidance (OG) and game theoretic guidance ( GTG ). One reason for this development is the fact that the implementation hardware for the guidance system has...state estimation techniques such as the Kalman Filter and others, it is now feasible to implement the OG, GTG and GTG +AI ‘intelligent’ guidance on...both PN and APN as special cases of OG and GTG ; this connection is further explored in this report. The desire to reduce weapon life-cycle cost

Collaborative Interactivity and Integrated Thinking in Brazilian Business Schools Using Cognitive Flexibility Hypertexts: The Panteon Project

ERIC Educational Resources Information Center

Lima, Marcos; Koehler, Matthew J.; Spiro, Rand J.

2004-01-01

In this article, we discuss how the Harvard Method of case study, Interactive Communication Technologies, and Cognitive Flexibility Theory may contribute to case-based learning about business decision-making. In particular, we are interested in designing learning environments that foster critical thinking, creativity, and reasoning that entertains…

Conflict monitoring in dual process theories of thinking.

PubMed

De Neys, Wim; Glumicic, Tamara

2008-03-01

Popular dual process theories have characterized human thinking as an interplay between an intuitive-heuristic and demanding-analytic reasoning process. Although monitoring the output of the two systems for conflict is crucial to avoid decision making errors there are some widely different views on the efficiency of the process. Kahneman [Kahneman, D. (2002). Maps of bounded rationality: A perspective on intuitive judgement and choice. Nobel Prize Lecture. Retrieved January 11, 2006, from: http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahnemann-lecture.pdf] and Evans [Evans, J. St. B. T. (1984). Heuristic and analytic processing in reasoning. British Journal of Psychology, 75, 451-468], for example, claim that the monitoring of the heuristic system is typically quite lax whereas others such as Sloman [Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3-22] and Epstein [Epstein, S. (1994). Integration of the cognitive and psychodynamic unconscious. American Psychologists, 49, 709-724] claim it is flawless and people typically experience a struggle between what they "know" and "feel" in case of a conflict. The present study contrasted these views. Participants solved classic base rate neglect problems while thinking aloud. In these problems a stereotypical description cues a response that conflicts with the response based on the analytic base rate information. Verbal protocols showed no direct evidence for an explicitly experienced conflict. As Kahneman and Evans predicted, participants hardly ever mentioned the base rates and seemed to base their judgment exclusively on heuristic reasoning. However, more implicit measures of conflict detection such as participants' retrieval of the base rate information in an unannounced recall test, decision making latencies, and the tendency to review the base rates indicated that the base rates had been thoroughly processed. On control problems where base rates and description did not conflict this was not the case. Results suggest that whereas the popular characterization of conflict detection as an actively experienced struggle can be questioned there is nevertheless evidence for Sloman's and Epstein's basic claim about the flawless operation of the monitoring. Whenever the base rates and description disagree people will detect this conflict and consequently redirect attention towards a deeper processing of the base rates. Implications for the dual process framework and the rationality debate are discussed.

Equations with Parameters: A Locus Approach

ERIC Educational Resources Information Center

Abramovich, Sergei; Norton, Anderson

2006-01-01

This paper introduces technology-based teaching ideas that facilitate the development of qualitative reasoning techniques in the context of quadratic equations with parameters. It reflects on activities designed for and used with prospective secondary mathematics teachers in accord with standards for teaching and recommendations for teachers in…

Teaching strategies to facilitate breast cancer screening by African-American women.

PubMed

Gibson, Lynette M

2008-12-01

The objective of this paper is to report on the recent literature concerning coverage of breast cancer epidemiology, the barriers to breast cancer screening, and the strategies to facilitate screening by African-American women. Based on these findings, the author suggests culturally appropriate techniques to be used to promote breast cancer screening in African-American women. Barriers to breast cancer screening in African-American women include emotional reasons, spiritual/religious reasons, fatalism, logistic concerns, lack of knowledge, and lack of follow-up by health-care professionals. Numerous strategies that have been targeted toward African-American women are reported. These include storytelling, witnessing, and testimonies; providing social support and having social support networks; and conducting multifaceted programs that include culturally specific breast health information. Based on the literature reviewed, the author suggests some examples of creative and culturally appropriate techniques that have been implemented with African-American women and that have resulted in positive feedback. These examples include the use of testimonies, photographs, prose, narratives, poetry, and quotations.

Case Studies of Secondary School Teachers Designing Socioscientific Issues-Based Instruction and Their Students' Socioscientific Reasoning

NASA Astrophysics Data System (ADS)

Karahan, Engin

Addressing socioscientific issues (SSI) has been one of the main focuses in science education since the Science, Technology, and Society (STS) movement in the 1970s (Levinson, 2006); however, teaching controversial socioscientific issues has always been challenging for teachers (Dillon, 1994; Osborne, Duschl, & Fairbrother, 2002). Although teachers exhibit positive attitudes for using controversial socioscientific issues in their science classrooms, only a small percentage of them actually incorporate SSI content into their science curricula on a regular basis (Sadler, Amirshokoohi, Kazempour, & Allspaw, 2006; Lee & Witz, 2009). The literature in science education has highlighted the signi?cant relationships among teacher beliefs, teaching practices, and student learning (Bryan & Atwater, 2002; King, Shumow, & Lietz, 2001; Lederman, 1992). Despite the fact that the case studies present a relatively detailed picture of teachers' values and motivations for teaching SSI (e.g. Lee, 2006; Lee & Witz, 2009; Reis & Galvao, 2004), these studies still miss the practices of these teachers and potential outcomes for their students. Therefore, there is a great need for in-depth case studies that would focus on teachers' practices of designing and teaching SSI-based learning environments, their deeper beliefs and motivations for teaching SSI, and their students' response to these practices (Lee, 2006). This dissertation is structured as three separate, but related, studies about secondary school teachers' experiences of designing and teaching SSI-based classes and their students' understanding of science and SSI reasoning. The case studies in this dissertation seek answers for (1) teachers' practices of designing and teaching SSI-based instruction, as well as its relation to their deeper personal beliefs and motivations to teach SSI, and (2) how their students respond to their approaches of teaching SSI in terms of their science understanding and SSI reasoning. The first paper presents case studies of three secondary science teachers within three high schools located along the Minnesota River Basin. The findings of this study documented the experiences of the participant teachers, as well as the contextual influences on those experiences. The second paper presents a case study of a science teacher and a social studies teacher which describes how these two teachers collaboratively designed and taught an environmental ethics class. The results of this study documented teachers' ways of sharing responsibilities, bringing their content and pedagogical expertise, and promoting the agency of their students in the environmental ethics class. The final paper in this dissertation presents case studies of secondary school students who were the participants in the SSI-based science classes described in the first two studies. The results of this study provided evidence for participant students' understanding of science and their socioscientific reasoning, as well as how they were influenced by the instructional decisions their teachers made.

78 FR 16783 - Approval and Promulgation of Implementation Plans; Georgia; Control Techniques Guidelines and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-19

... Promulgation of Implementation Plans; Georgia; Control Techniques Guidelines and Reasonably Available Control...), related to reasonably available control technology (RACT) requirements. This correcting amendment corrects... October 21, 2009, SIP submittal for certain source categories for which EPA has issued control technique...

V and V of ISHM Software for Space Exploration

NASA Technical Reports Server (NTRS)

Markosian, Lawrence; Feather, Martin, S.; Brinza, David; Figueroa, F.

2005-01-01

NASA has established a far-reaching and long-term program for robotic and manned exploration of the solar system, beginning with missions to the moon and Mars. The Crew Transportation System (CTS), a key system for space exploration, imposes four requirements' that ISHM addresses. These requirements have a wide range of implications for V&V and certification of ISHM. There is a range of time-criticality for ISHM actions, from prognostication, which is often (but not always) non-time-critical, to time-critical state estimation and system management under off-nominal emergency conditions. These are externally imposed requirements on ISHM that are subject to V&V. - In addition, a range of techniques are needed to implement an ISHM. The approaches to ISHM are described elsewhere. These approaches range from well-understood algorithms for low-level data analysis, validation and reporting, to AI techniques for state estimation and planning. The range of techniques, and specifically the use of AI techniques such as reasoning under uncertainty and mission planning (and re-planning), implies that several V&V approaches may be required. Depending on the ISHM architecture, traditional testing approaches may be adequate for some ISHM functionality. The AI-based approaches to reasoning under uncertainty, model-based reasoning, and planning share characteristics typical of other complex software systems, but they also have characteristics that set them apart and challenge standard V&V techniques. The range of possible solutions to the overall ISHM problem impose internal challenges to V&V. The V&V challenges increase when hard real-time constraints are imposed for time-critical functionality. For example, there is an external requirement that impending catastrophic failure of the Launch Vehicle (LV) at launch time be detected and life-saving action be taken within two seconds. In this paper we outline the challenges for ISHM V&V, existing approaches and analogs in other software application areas, and possible new approaches to the V&V challenges for space exploration ISHM.

Content-related interactions and methods of reasoning within self-initiated organic chemistry study groups

NASA Astrophysics Data System (ADS)

Christian, Karen Jeanne

2011-12-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of content processing, and types of reasoning processes used by students within their groups. Our analysis showed that groups engaged in predominantly three types of interactions when discussing chemistry content: co-construction, teaching, and tutoring. Although each group engaged in each of these types of interactions at some point, their prevalence varied between groups and group members. Our analysis suggests that the types of interactions that were most common depended on the relative content knowledge of the group members as well as on the difficulty of the tasks in which they were engaged. Additionally, we were interested in characterizing the reasoning methods used by students within their study groups. We found that students used a combination of three content-relevant methods of reasoning: model-based reasoning, case-based reasoning, or rule-based reasoning, in conjunction with one chemically-irrelevant method of reasoning: symbol-based reasoning. The most common way for groups to reason was to use rules, whereas the least common way was for students to work from a model. In general, student reasoning correlated strongly to the subject matter to which students were paying attention, and was only weakly related to student interactions. Overall, results from this study may help instructors to construct appropriate tasks to guide what and how students study outside of the classroom. We found that students had a decidedly strategic approach in their study groups, relying heavily on material provided by their instructors, and using the reasoning strategies that resulted in the lowest levels of content processing. We suggest that instructors create more opportunities for students to explore model-based reasoning, and to create opportunities for students to be able to co-construct in a collaborative manner within the context of their organic chemistry course.

Teaching and Assessing Clinical Reasoning Skills.

PubMed

Modi, Jyoti Nath; Anshu; Gupta, Piyush; Singh, Tejinder

2015-09-01

Clinical reasoning is a core competency expected to be acquired by all clinicians. It is the ability to integrate and apply different types of knowledge, weigh evidence critically and reflect upon the process used to arrive at a diagnosis. Problems with clinical reasoning often occur because of inadequate knowledge, flaws in data gathering and improper approach to information processing. Some of the educational strategies which can be used to encourage acquisition of clinical reasoning skills are: exposure to a wide variety of clinical cases, activation of previous knowledge, development of illness scripts, sharing expert strategies to arrive at a diagnosis, forcing students to prioritize differential diagnoses; and encouraging reflection, metacognition, deliberate practice and availability of formative feedback. Assessment of clinical reasoning abilities should be done throughout the training course in diverse settings. Use of scenario based multiple choice questions, key feature test and script concordance test are some ways of theoretically assessing clinical reasoning ability. In the clinical setting, these skills can be tested in most forms of workplace based assessment. We recommend that clinical reasoning must be taught at all levels of medical training as it improves clinician performance and reduces cognitive errors.

Actions of cholera toxin and the prevention and treatment of cholera

NASA Astrophysics Data System (ADS)

Holmgren, Jan

1981-07-01

The drastic intestinal secretion of fluid and electrolytes that is characteristic of cholera is the result of reasonably well understood cellular and biochemical actions of the toxin secreted by Vibrio cholerae. Based on this understanding it is possible to devise new techniques for the treatment and prophylaxis of cholera to complement those based on fluid replacement therapy and sanitation.

Systematizing Scaffolding for Problem-Based Learning: A View from Case-Based Reasoning

ERIC Educational Resources Information Center

Tawfik, Andrew A.; Kolodner, Janet L.

2016-01-01

Current theories and models of education often argue that instruction is best administered when knowledge is situated within a context. Problem-based learning (PBL) provides an approach to education that has particularly powerful affordances for learning disciplinary content and practices by solving authentic problems within a discipline. However,…

Organising the Chemistry of Question-Based Learning: A Case Study

ERIC Educational Resources Information Center

de Jesus, Helena Pedrosa; de Souza, Francisle Neri; Teixeira-Dias, Jose J. C.; Watts, Mike

2005-01-01

Designing inquiry-based-learning with and for university students develops problem-solving skills and logical reasoning, as well as reflective thinking. It involves working as a member of a team, questioning, being creative, shaping the skills for continued intellectual development. It is argued that inquiry-based group work is one of the most…

Influx: A Tool and Framework for Reasoning under Uncertainty

DTIC Science & Technology

2015-09-01

Interfaces to external programs Not all types of problems are naturally suited to being entirely modelled and implemented within Influx1. In general... development pertaining to the implementation of the reasoning tool and specific applications are not included in this document. RELEASE LIMITATION...which case a probability is supposed to reflect the subjective belief of an agent for the problem at hand ( based on its experience and/or current state

Purpose, Processes, Partnerships, and Products: 4Ps to advance Participatory Socio-Environmental Modeling

NASA Astrophysics Data System (ADS)

Gray, S. G.; Voinov, A. A.; Jordan, R.; Paolisso, M.

2016-12-01

Model-based reasoning is a basic part of human understanding, decision-making, and communication. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding environmental change since stakeholders often hold valuable knowledge about socio-environmental dynamics and since collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four dimensional framework that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of environmental changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of environmental policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques.

PubMed

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

The role of complex emotions in inconsistent diagnoses of schizophrenia.

PubMed

Gara, Michael A; Vega, William A; Lesser, Ira; Escamilla, Michael; Lawson, William B; Wilson, Daniel R; Fleck, David E; Strakowski, Stephen M

2010-09-01

In the case of large-scale epidemiological studies, there is evidence of substantial disagreement when lay diagnoses of schizophrenia based on structured interviews are compared with expert diagnoses of the same patients. Reasons for this level of disagreement are investigated in the current study, which made use of advances in text-mining techniques and associated structural representations of language expressions. Specifically, the current study examined whether content analyses of transcribed diagnostic interviews obtained from 150 persons with serious psychiatric disorders yielded any discernable patterns that correlated with diagnostic inconsistencies of schizophrenia. In summary, it was found that the patterning or structure of spontaneous self-reports of emotion states in the diagnostic interview was associated with diagnostic inconsistencies of schizophrenia, irrespective of confounders; i.e., age of patient, gender, or ethnicity. In particular, complex emotion patterns were associated with greater disagreement between experts and trained lay interviewers than were simpler patterns.

Diffusion processes in tumors: A nuclear medicine approach

NASA Astrophysics Data System (ADS)

Amaya, Helman

2016-07-01

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and 18F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer software was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical 18F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.

Model Updating of Complex Structures Using the Combination of Component Mode Synthesis and Kriging Predictor

PubMed Central

Li, Yan; Wang, Dejun; Zhang, Shaoyi

2014-01-01

Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM). Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS) technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM) to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters. PMID:24634612

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques

PubMed Central

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Background: Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. Methods: In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Results: Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Conclusions: Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images. PMID:29535920

Airport and superficial femoral artery obstruction due to a wandering coronary stent: the possibility of airport detection of modern implant metals.

PubMed

Teijink, J A W; van Herwaarden, J A; van den Berg, J C; Overtoom, T C; Moll, F L

2004-06-01

In the treatment of coronary artery disease, peripheral loss of a coronary stent is an unusual complication. We present the case of a patient who suggested that his right leg claudication was caused by a slipped coronary stent 2 years previously. The patient was convinced about this unusual finding based on an airport security check. Examination proved him to be right. However, the ability to detect an object using eddy currents is dependent on the object's permeability and its conductivity. Ferrous (iron) content is not the critical factor. Modern implant materials and processing techniques result in implants that are difficult to magnetize i.e. their permeability is very low. In addition their conductivity is very low. This enables modern implants to escape detection at airports. For this reason the event at the airport, as described by our patient, is considered coincidental.

Dynamic analysis for solid waste management systems: an inexact multistage integer programming approach.

PubMed

Li, Yongping; Huang, Guohe

2009-03-01

In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability.

PubMed

Ahn, Jae Joon; Kim, Young Min; Yoo, Keunje; Park, Joonhong; Oh, Kyong Joo

2012-11-01

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.

Digital processing of satellite imagery application to jungle areas of Peru

NASA Technical Reports Server (NTRS)

Pomalaza, J. C. (Principal Investigator); Pomalaza, C. A.; Espinoza, J.

1976-01-01

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Measuring Surface Deformation in Glacier Retreated Areas Based on Ps-Insar - Geladandong Glacier as a Case Study

NASA Astrophysics Data System (ADS)

Mohamadi, B.; Balz, T.

2018-04-01

Glaciers are retreating in many parts of the world as a result of global warming. Many researchers consider Qinghai-Tibetan Plateau as a reference for climate change by measuring glaciers retreat on the plateau. This retreat resulted in some topographic changes in retreated areas, and in some cases can lead to geohazards as landslides, and rock avalanches, which is known in glacier retreated areas as paraglacial slope failure (PSF). In this study, Geladandong biggest and main glacier mass was selected to estimate surface deformation on its glacier retreated areas and define potential future PSF based on PS-InSAR technique. 56 ascending and 49 descending images were used to fulfill this aim. Geladandong glacier retreated areas were defined based on the maximum extent of the glacier in the little ice age. Results revealed a general uplift in the glacier retreated areas with velocity less than 5mm/year. Obvious surface motion was revealed in seven parts surround glacier retreated areas with high relative velocity reached ±60mm/year in some parts. Four parts were considered as PSF potential motion, and two of them showed potential damage for the main road in the study area in case of rock avalanche into recent glacier lakes that could result in glacier lake outburst flooding heading directly to the road. Finally, further analysis and field investigations are needed to define the main reasons for different types of deformation and estimate future risks of these types of surface motion in the Qinghai-Tibetan Plateau.

Intelligent fault management for the Space Station active thermal control system

NASA Technical Reports Server (NTRS)

Hill, Tim; Faltisco, Robert M.

1992-01-01

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed Central

LeBozec, C.; Jaulent, M. C.; Zapletal, E.; Degoulet, P.

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users. Images Figure 6 Figure 7 PMID:9929346

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed

LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

Using Bayesian networks to guide the assessment of new evidence in an appeal case

PubMed Central

Smit, Nadine M.; Lagnado, David A.; Morgan, Ruth M.; Fenton, Norman E.

2016-01-01

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future. PMID:27376015

Using Bayesian networks to guide the assessment of new evidence in an appeal case.

PubMed

Smit, Nadine M; Lagnado, David A; Morgan, Ruth M; Fenton, Norman E

2016-05-25

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future.

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2014 CFR

2014-01-01

... alternative liquid automotive fuels other than biodiesel blends and biomass-based diesel blends, you must... of biodiesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biodiesel contained in the fuel, and in the case of biomass-based diesel...

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2013 CFR

2013-01-01

... alternative liquid automotive fuels other than biodiesel blends and biomass-based diesel blends, you must... of biodiesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biodiesel contained in the fuel, and in the case of biomass-based diesel...

16 CFR 306.5 - Automotive fuel rating.

Code of Federal Regulations, 2012 CFR

2012-01-01

... alternative liquid automotive fuels other than biodiesel blends and biomass-based diesel blends, you must... of biodiesel blends, you must possess a reasonable basis, consisting of competent and reliable evidence, for the percentage of biodiesel contained in the fuel, and in the case of biomass-based diesel...

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

Enhanced sludge dewatering by electrofiltration. A feasibility study.

PubMed

Saveyn, H; Huybregts, L; Van der Meeren, P

2001-01-01

Sludge treatment is a major issue in today's waste water treatment. One of the problems encountered is the limiting dewaterability of mainly biological sludges, causing high final treatment costs for incineration or landfill. Although during recent years, improvements are realised in the field of dewatering, the actual dry solids content after dewatering remains at a maximum value of about 35%. In order to increase the dry solids content, the technique of electrofiltration was investigated. Electrofiltration is the combination of two known techniques, traditional pressure filtration and electroosmotic/electrophoretic dewatering. Pressure filtration is based on pressure as the driving force for dewatering a sludge. Limitations hereby lie in the clogging of the filter cloth due to the build-up of the filtercake. Electroosmotic/electrophoretic dewatering is based on an electric field to separate sludge colloid particles from the surrounding liquid by placing the sludge liquor between two oppositely charged electrodes. In this case, mobile sludge particles will move to one electrode due to their natural surface charge, and the liquid phase will be collected at the oppositely charged electrode. Combination of both techniques makes it possible to create a more homogeneous filter cake and prevent the filter from clogging, resulting in higher cake dry solids contents and shorter filtration cycles. To investigate the feasibility of this technique for the dewatering of activated sludge, a filter unit was developed for investigations on lab scale. Multiple dewatering tests were performed in which the electric parameters for electrofiltration were varied. It was derived from these experiments that very high filter cake dry solids contents (to more than 60%), and short filtration cycles were attainable by using a relatively small electric DC field. The power consumption was very low compared to the power needed to dewater sludge by thermal drying techniques. For this reason, this technique seems very promising for the dewatering of biological sludges.

The importance of calorimetry for highly-boosted jet substructure

DOE PAGES

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas; ...

2018-01-09

Here, jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstratemore » physics contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

The importance of calorimetry for highly-boosted jet substructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas

2017-09-25

Jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstrate physicsmore » contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

The importance of calorimetry for highly-boosted jet substructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas

Here, jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstratemore » physics contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

Image Analysis via Soft Computing: Prototype Applications at NASA KSC and Product Commercialization

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve

2011-01-01

This slide presentation reviews the use of "soft computing" which differs from "hard computing" in that it is more tolerant of imprecision, partial truth, uncertainty, and approximation and its use in image analysis. Soft computing provides flexible information processing to handle real life ambiguous situations and achieve tractability, robustness low solution cost, and a closer resemblance to human decision making. Several systems are or have been developed: Fuzzy Reasoning Edge Detection (FRED), Fuzzy Reasoning Adaptive Thresholding (FRAT), Image enhancement techniques, and visual/pattern recognition. These systems are compared with examples that show the effectiveness of each. NASA applications that are reviewed are: Real-Time (RT) Anomaly Detection, Real-Time (RT) Moving Debris Detection and the Columbia Investigation. The RT anomaly detection reviewed the case of a damaged cable for the emergency egress system. The use of these techniques is further illustrated in the Columbia investigation with the location and detection of Foam debris. There are several applications in commercial usage: image enhancement, human screening and privacy protection, visual inspection, 3D heart visualization, tumor detections and x ray image enhancement.

Experimental analysis of electrical properties of composite materials

NASA Astrophysics Data System (ADS)

Fiala, L.; Rovnaník, P.; Černý, R.

2017-02-01

Dry cement-based composites are electrically non-conductive materials that behave in electric field like dielectrics. However, a relatively low amount of electrically conductive admixture significantly increases the electrical conductivity which extends applicability of such materials in practice. Therefore, they can be used as self-monitoring sensors controlling development of cracks; as sensors monitoring moisture content or when treated by an external electrical voltage as heat sources used for deicing of material's surface layer. Alkali-activated aluminosilicates (AAA), as competing materials to cement-based materials, are intensively investigated in the present due to their superior durability and environmental impact. Whereas the electrical properties of AAA are similar to those cement-based, they can be enhanced in the same way. In both cases, it is crucial to find a reasonable amount of electrically conductive phase to design composites with a sufficient electrical conductivity at an affordable price. In this paper, electrical properties of composites based on AAA binder and electrically conductive admixture represented by carbon nanotubes (CNT) are investigated. Measurements of electrical properties are carried out by means of 2-probes DC technique on nine types of samples; reference sample without the conductive phase and samples with CNT admixture in amount of 0.1 % - 2.5 % by vol. A significant increase of the electrical conductivity starts from the amount of 0.5 % CNT admixture and in case of 2.5 % CNT is about three orders of magnitude higher compared to the reference sample.

The correlation between concept mastery and stage of moral reasoning student using socio-scientific issues on reproductive system material

NASA Astrophysics Data System (ADS)

Lestari, T. A.; Saefudin; Priyandoko, D.

2018-05-01

This research aims to analyze the correlation between concept mastery and moral stages of students. The research method using a correlational study with stratified random sampling technique. The population in this research is all of eleventh grade students in Senior High School Bandung. Data were collected from 297 eleventh grade students of three Senior High School in Bandung with use the instrument in the form of examination and stage of moral reasoning questionnaire. The stage of moral reasoning in this research consists of two student’s moral reasoning categories based on 16 questionnaire as the indicators from Jones et al. (2007). The results of this research shows that the average of eleventh grade student’s moral reasoning stage is the advanced stage. The results of this research shows that the concept mastery and the stage of moral reasoning indicates that there are 0.370 0f a positive correlation. This research provides an overview of eleventh grade student about concept mastery and stage of moral reasoning using socio-scientific issues.

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Improving the learning of clinical reasoning through computer-based cognitive representation

PubMed Central

Wu, Bian; Wang, Minhong; Johnson, Janice M.; Grotzer, Tina A.

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

NASA Astrophysics Data System (ADS)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.

Distributed Deliberative Recommender Systems

NASA Astrophysics Data System (ADS)

Recio-García, Juan A.; Díaz-Agudo, Belén; González-Sanz, Sergio; Sanchez, Lara Quijano

Case-Based Reasoning (CBR) is one of most successful applied AI technologies of recent years. Although many CBR systems reason locally on a previous experience base to solve new problems, in this paper we focus on distributed retrieval processes working on a network of collaborating CBR systems. In such systems, each node in a network of CBR agents collaborates, arguments and counterarguments its local results with other nodes to improve the performance of the system's global response. We describe D2ISCO: a framework to design and implement deliberative and collaborative CBR systems that is integrated as a part of jcolibritwo an established framework in the CBR community. We apply D2ISCO to one particular simplified type of CBR systems: recommender systems. We perform a first case study for a collaborative music recommender system and present the results of an experiment of the accuracy of the system results using a fuzzy version of the argumentation system AMAL and a network topology based on a social network. Besides individual recommendation we also discuss how D2ISCO can be used to improve recommendations to groups and we present a second case of study based on the movie recommendation domain with heterogeneous groups according to the group personality composition and a group topology based on a social network.

Peroral endoscopic myotomy (POEM) for treating esophageal motility disorders

PubMed Central

Wong, Ian

2017-01-01

Pneumatic dilatation and Heller myotomy have been thoroughly studied as the most viable treatment options for achalasia. The pendulum, however, is shifting to the minimally invasive approach. Since Inoue et al. published the experience of the first 17 cases of peroral endoscopic myotomy (POEM) in 2010, there have been at least 5,000 cases performed worldwide and the number is increasing exponentially. Experts across the globe have been extending the indications to various esophageal motility disorders, to patients of extremes of age, sigmoidal esophagus and re-operated patients. There are a few variations in technique across different centers in defining the gastroesophageal junction (GEJ) and adequacy of myotomy, the optimal length, site of myotomy and whether the full thickness of the muscle wall should be cut. Large case series demonstrated its promising efficacy & reasonable complication profile. Randomized controlled trial in comparison with the gold standard, Heller myotomy, is ongoing. The future application of submucosal tunnelling technique is thrilling with its extension in tumour resection, antropyloromyotomy and other natural orifice transluminal endoscopic surgery (NOTES). PMID:28616407

Abdominal emergencies in pediatrics.

PubMed

Coca Robinot, D; Liébana de Rojas, C; Aguirre Pascual, E

2016-05-01

Abdominal symptoms are among the most common reasons for pediatric emergency department visits, and abdominal pain is the most frequently reported symptom. Thorough history taking and physical examination can often reach the correct diagnosis. Knowing the abdominal conditions that are most common in each age group can help radiologists narrow the differential diagnosis. When imaging tests are indicated, ultrasonography is usually the first-line technique, enabling the diagnosis or adding relevant information with the well-known advantages of this technique. Nowadays, plain-film X-ray studies are reserved for cases in which perforation, bowel obstruction, or foreign body ingestion is suspected. It is also important to remember that abdominal pain can also occur secondary to basal pneumonia. CT is reserved for specific indications and in individual cases, for example, in patients with high clinical suspicion of abdominal disease and inconclusive findings at ultrasonography. We review some of the most common conditions in pediatric emergencies, the different imaging tests indicated in each case, and the imaging signs in each condition. Copyright © 2016 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

[Current radionuclear methods in the diagnosis of regional myocardial circulation disorders].

PubMed

Felix, R; Winkler, C

1977-01-29

Among nuclear medical diagnostic procedures a distinction can be made between non-invasive and invasive methods. The non-invasive methods serve either to image the still viable myocardium ("cold spot" technique) or for direct visualization of recently infarcted myocardial tissue ("hot spot" technique). These methods have the advantage of simple handling and good reproducibility. Side effects and risks are thus far unknown. Improvement of local dissolution should be aimed at in the future and wound greatly increase diagnostic and topographic security. The invasive procedures always require catheterization of the coronary arteries. This is the reason why they can be performed only with coronary arteriography. The Xenon "wash out" technique permits, with some restrictions, quantitative measurement of the regional flow rate. The "inflow technique" permits determination of perfusion distribution. The possibilities of the "double-radionuclide" scintigramm are discussed. For measurement of activity distribution, sationary detectors are generally preferred. In the case of the time-activity curves with the Xenon "wash out" technique, single detectors offer certain advantages.

The role of ethics in information technology decisions: a case-based approach to biomedical informatics education.

PubMed

Anderson, James G

2004-03-18

The purpose of this paper is to propose a case-based approach to instruction regarding ethical issues raised by the use of information technology (IT) in healthcare. These issues are rarely addressed in graduate degree and continuing professional education programs in health informatics. There are important reasons why ethical issues need to be addressed in informatics training. Ethical issues raised by the introduction of information technology affect practice and are ubiquitous. These issues are frequently among the most challenging to young practitioners who are ill prepared to deal with them in practice. First, the paper provides an overview of methods of moral reasoning that can be used to identify and analyze ethical problems in health informatics. Second, we provide a framework for defining cases that involve ethical issues and outline major issues raised by the use of information technology. Specific cases are used as examples of new dilemmas that are posed by the introduction of information technology in healthcare. These cases are used to illustrate how ethics can be integrated with the other elements of informatics training. The cases discussed here reflect day-to-day situations that arise in health settings that require decisions. Third, an approach that can be used to teach ethics in health informatics programs is outlined and illustrated.

Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steven J.

2004-01-01

A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

Single-Case Analysis to Determine Reasons for Failure of Behavioral Treatment via Telehealth

ERIC Educational Resources Information Center

Schieltz, Kelly M.; Romani, Patrick W.; Wacker, David P.; Suess, Alyssa N.; Huang, Pei; Berg, Wendy K.; Lindgren, Scott D.; Kopelman, Todd G.

2018-01-01

Functional communication training (FCT) is a widely used and effective function-based treatment for problem behavior. The purpose of this article is to present two cases in which FCT was unsuccessful in reducing the occurrence of problem behavior displayed by two young children with an autism spectrum disorder. Both children received the same…

Learning to Think Spatially in an Undergraduate Interdisciplinary Computational Design Context: A Case Study

ERIC Educational Resources Information Center

Ben Youssef, Belgacem; Berry, Barbara

2012-01-01

Spatial thinking skills are vital for success in everyday living and work, not to mention the centrality of spatial reasoning in scientific discoveries, design-based disciplines, medicine, geosciences and mathematics to name a few. This case study describes a course in spatial thinking and communicating designed and delivered by an…

Differences in clinical reasoning among nurses working in highly specialised paediatric care.

PubMed

Andersson, Nina; Klang, Birgitta; Petersson, Gunilla

2012-03-01

The aim of the study was to examine differences in clinical reasoning among novice, experienced and specialist paediatric nurses. Highly specialised paediatric care requires specific knowledge and ongoing skill performance of the nurses employed. There is a lack of research in how paediatric nurses manage the daily care problems they encounter and how they acquire the skills required to give patients the best possible care. More knowledge is needed about how paediatric nurses with different experience and education reason and communicate about paediatric patient situations. The study was based on six recorded group discussions of a fictitious, but realistic paediatric case. Three categories of nurses: novices (n = 7), experienced (n = 7) and specialists (n = 7) from a paediatric hospital participated. A qualitative content analysis approach was chosen to examine differences in clinical reasoning. Several themes were uncovered: child's social situation, child abuse and the child's illness, qualitative differences emerged in how the nurses discussed the case. Three approaches were identified: a task-oriented approach (novices and experienced), an action-oriented approach (novices and experienced) and hypothesis-oriented approach (specialists) while discussing the case. When comparing nurses in three competence groups, it was established that the groups with extensive experience and specialist education reasoned differently than the other groups. Between the novice and experienced groups, no obvious differences were found. Thus, the importance of experience alone for the development of competence is still an open question. Experience combined with further education appears important for developing professional competence in paediatric care. Nurses' reasoning in clinical paediatric care is related to experience and training. © 2012 Blackwell Publishing Ltd.

Reasoning Based Quality Assurance of Medical Ontologies: A Case Study

PubMed Central

Horridge, Matthew; Parsia, Bijan; Noy, Natalya F.; Musenm, Mark A.

2014-01-01

The World Health Organisation is using OWL as a key technology to develop ICD-11 – the next version of the well-known International Classification of Diseases. Besides providing better opportunities for data integration and linkages to other well-known ontologies such as SNOMED-CT, one of the main promises of using OWL is that it will enable various forms of automated error checking. In this paper we investigate how automated OWL reasoning, along with a Justification Finding Service can be used as a Quality Assurance technique for the development of large and complex ontologies such as ICD-11. Using the International Classification of Traditional Medicine (ICTM) – Chapter 24 of ICD-11 – as a case study, and an expert panel of knowledge engineers, we reveal the kinds of problems that can occur, how they can be detected, and how they can be fixed. Specifically, we found that a logically inconsistent version of the ICTM ontology could be repaired using justifications (minimal entailing subsets of an ontology). Although over 600 justifications for the inconsistency were initially computed, we found that there were three main manageable patterns or categories of justifications involving TBox and ABox axioms. These categories represented meaningful domain errors to an expert panel of ICTM project knowledge engineers, who were able to use them to successfully determine the axioms that needed to be revised in order to fix the problem. All members of the expert panel agreed that the approach was useful for debugging and ensuring the quality of ICTM. PMID:25954373

Increasing the Runtime Speed of Case-Based Plan Recognition

DTIC Science & Technology

2015-05-01

number of situations that the robot might reasonably be expected to encounter. This requires ef- ficient indexing schemes to ensure that plan retrieval...collection of information if it does not display a currently valid OMB control number . 1. REPORT DATE MAY 2015 2. REPORT TYPE 3. DATES COVERED 00...00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Increasing the Runtime Speed of Case-Based Plan Recognition 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Unstable metacarpal and phalangeal fractures: treatment by internal fixation using AO mini-fragment plates and screws.

PubMed

Mumtaz, Mohammad Umar; Farooq, Muneer Ahmad; Rasool, Altaf Ahmad; Kawoosa, Altaf Ahmad; Badoo, Abdul Rashid; Dhar, Shabir Ahmad

2010-07-01

Accurate open reduction and internal fixation for metacarpal and phalangeal fractures of the hand is required in less than 5% of the patients; otherwise, closed treatment techniques offer satisfactory results in most of these cases as these fractures are stable either before or after closed reduction. AO mini-fragment screws and plates, when used in properly selected cases, can provide rigid fixation, allowing early mobilization of joints and hence good functional results while avoiding problems associated with protruding K-wires and immobilization. The advantages of such internal fixation urged us to undertake such a study in our state where such hand injuries are commonly seen. Forty patients with 42 unstable metacarpal and phalangeal fractures were treated with open reduction and internal fixation using AO mini-fragment screws and plates over a period of three years in a prospective manner. The overall results were good in 78.5% of cases, fair in 19% of cases and poor in 2.5% of cases, as judged according to the criteria of the American Society for Surgery of the Hand. This technique is a reasonable option for treating unstable metacarpal and phalangeal fractures as it provides a highly rigid fixation, which is sufficient to allow early mobilization of the adjacent joints, thus helping to achieve good functional results.

Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders

PubMed Central

Chiba, Yasutaka

2014-01-01

Questions of mediation are often of interest in reasoning about mechanisms, and methods have been developed to address these questions. However, these methods make strong assumptions about the absence of confounding. Even if exposure is randomized, there may be mediator-outcome confounding variables. Inference about direct and indirect effects is particularly challenging if these mediator-outcome confounders are affected by the exposure because in this case these effects are not identified irrespective of whether data is available on these exposure-induced mediator-outcome confounders. In this paper, we provide a sensitivity analysis technique for natural direct and indirect effects that is applicable even if there are mediator-outcome confounders affected by the exposure. We give techniques for both the difference and risk ratio scales and compare the technique to other possible approaches. PMID:25580387

Dynamic test input generation for multiple-fault isolation

NASA Technical Reports Server (NTRS)

Schaefer, Phil

1990-01-01

Recent work is Causal Reasoning has provided practical techniques for multiple fault diagnosis. These techniques provide a hypothesis/measurement diagnosis cycle. Using probabilistic methods, they choose the best measurements to make, then update fault hypotheses in response. For many applications such as computers and spacecraft, few measurement points may be accessible, or values may change quickly as the system under diagnosis operates. In these cases, a hypothesis/measurement cycle is insufficient. A technique is presented for a hypothesis/test-input/measurement diagnosis cycle. In contrast to generating tests a priori for determining device functionality, it dynamically generates tests in response to current knowledge about fault probabilities. It is shown how the mathematics previously used for measurement specification can be applied to the test input generation process. An example from an efficient implementation called Multi-Purpose Causal (MPC) is presented.

Developing Metacognition: A Basis for Active Learning

ERIC Educational Resources Information Center

Vos, Henk; de Graaff, E.

2004-01-01

The reasons to introduce formats of active learning in engineering (ALE) such as project work, problem-based learning, use of cases, etc. are mostly based on practical experience, and sometimes from applied research on teaching and learning. Such research shows that students learn more and different abilities than in traditional formats of…

Hybrid Filtering in Semantic Query Processing

ERIC Educational Resources Information Center

Jeong, Hanjo

2011-01-01

This dissertation presents a hybrid filtering method and a case-based reasoning framework for enhancing the effectiveness of Web search. Web search may not reflect user needs, intent, context, and preferences, because today's keyword-based search is lacking semantic information to capture the user's context and intent in posing the search query.…

[Acquiring skills in malignant hyperthermia crisis management: comparison of high-fidelity simulation versus computer-based case study].

PubMed

Mejía, Vilma; Gonzalez, Carlos; Delfino, Alejandro E; Altermatt, Fernando R; Corvetto, Marcia A

The primary purpose of this study was to compare the effect of high fidelity simulation versus a computer-based case solving self-study, in skills acquisition about malignant hyperthermia on first year anesthesiology residents. After institutional ethical committee approval, 31 first year anesthesiology residents were enrolled in this prospective randomized single-blinded study. Participants were randomized to either a High Fidelity Simulation Scenario or a computer-based Case Study about malignant hyperthermia. After the intervention, all subjects' performance in was assessed through a high fidelity simulation scenario using a previously validated assessment rubric. Additionally, knowledge tests and a satisfaction survey were applied. Finally, a semi-structured interview was done to assess self-perception of reasoning process and decision-making. 28 first year residents finished successfully the study. Resident's management skill scores were globally higher in High Fidelity Simulation versus Case Study, however they were significant in 4 of the 8 performance rubric elements: recognize signs and symptoms (p = 0.025), prioritization of initial actions of management (p = 0.003), recognize complications (p = 0.025) and communication (p = 0.025). Average scores from pre- and post-test knowledge questionnaires improved from 74% to 85% in the High Fidelity Simulation group, and decreased from 78% to 75% in the Case Study group (p = 0.032). Regarding the qualitative analysis, there was no difference in factors influencing the student's process of reasoning and decision-making with both teaching strategies. Simulation-based training with a malignant hyperthermia high-fidelity scenario was superior to computer-based case study, improving knowledge and skills in malignant hyperthermia crisis management, with a very good satisfaction level in anesthesia residents. Copyright © 2018 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

Simple methods of exploiting the underlying structure of rule-based systems

NASA Technical Reports Server (NTRS)

Hendler, James

1986-01-01

Much recent work in the field of expert systems research has aimed at exploiting the underlying structures of the rule base for reasons of analysis. Such techniques as Petri-nets and GAGs have been proposed as representational structures that will allow complete analysis. Much has been made of proving isomorphisms between the rule bases and the mechanisms, and in examining the theoretical power of this analysis. In this paper we describe some early work in a new system which has much simpler (and thus, one hopes, more easily achieved) aims and less formality. The technique being examined is a very simple one: OPS5 programs are analyzed in a purely syntactic way and a FSA description is generated. In this paper we describe the technique and some user interface tools which exploit this structure.

Percutaneous Transhepatic Portography for the Treatment of Early Portal Vein Thrombosis After Surgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adani, Gian Luigi, E-mail: adanigl@hotmail.com; Baccarani, Umberto; Risaliti, Andrea

2007-11-15

We treated three cases of early portal vein thrombosis (PVT) by minimally invasive percutaneous transhepatic portography. All patients developed PVT within 30 days of major hepatic surgery (one case each of orthotopic liver transplantation, splenectomy in a previous liver transplant recipient, and right extended hepatectomy with resection and reconstruction of the left branch of the portal vein for tumor infiltration). In all cases minimally invasive percutaneous transhepatic portography was adopted to treat this complication by mechanical fragmentation and pharmacological lysis of the thrombus. A vascular stent was also positioned in the two cases in which the thrombosis was related tomore » a surgical technical problem. Mechanical fragmentation of the thrombus with contemporaneous local urokinase administration resulted in complete removal of the clot and allowed restoration of normal blood flow to the liver after a median follow-up of 37 months. PVT is an uncommon but severe complication after major surgery or liver transplantation. Surgical thrombectomy, with or without reconstruction of the portal vein, and retransplantation are characterized by important surgical morbidity and mortality. Based on our experience, minimally invasive percutaneous transhepatic portography should be considered an option toward successful recanalization of early PVT after major liver surgery including transplantation. Balloon dilatation and placement of a vascular stent could help to decrease the risk of recurrent thrombosis when a defective surgical technique is the reason for the thrombosis.« less

Intertwining evidence- and model-based reasoning in physics sensemaking: An example from electrostatics

NASA Astrophysics Data System (ADS)

Russ, Rosemary S.; Odden, Tor Ole B.

2017-12-01

Our field has long valued the goal of teaching students not just the facts of physics, but also the thinking and reasoning skills of professional physicists. The complexity inherent in scientific reasoning demands that we think carefully about how we conceptualize for ourselves, enact in our classes, and encourage in our students the relationship between the multifaceted practices of professional science. The current study draws on existing research in the philosophy of science and psychology to advocate for intertwining two important aspects of scientific reasoning: using evidence from experimentation and modeling. We present a case from an undergraduate physics course to illustrate how these aspects can be intertwined productively and describe specific ways in which these aspects of reasoning can mutually reinforce one another in student learning. We end by discussing implications for this work for instruction in introductory physics courses and for research on scientific reasoning at the undergraduate level.

Sterilization by Cooling in Isochoric Conditions: The Case of Escherichia coli

PubMed Central

Salinas-Almaguer, Samuel; Angulo-Sherman, Abril; Sierra-Valdez, Francisco Javier; Mercado-Uribe, Hilda

2015-01-01

High hydrostatic pressure (HHP) affects the structure, metabolism and survival of micro-organisms including bacteria. For this reason HHP is a promising treatment in the food industry. The aim of this work is to evaluate the effect of high pressure, under isochoric cooling conditions, on Escherichia coli, where such high pressure develops due to the fact water cannot expand. We combine survival curves obtained by spectrophotometry and images of atomic force microscopy in this study. Our results show that cooling at -20 and -30°C leads to a partial destruction of a Escherichia coli population. However, cooling at -15°C causes a total extermination of bacteria. This intriguing result is explained by the phase diagram of water. In the first case, the simultaneous formation of ice III and ice Ih crystals provides a safe environment for bacteria. In the second case (-15°C) Escherichia coli remains in a metastable and amorphous free-of-crystals liquid subjected to high pressure. Our work is the first experimental study carried out to inactivate Escherichia coli under isochoric cooling conditions. Unlike HHP, which is based on the application of an external load to augment the pressure, this technique only requires cooling. The method could be used for annihilation of other Escherichia coli strains and perhaps other micro-organisms. PMID:26480032

Learner-Centered Environments: Creating Effective Strategies Based on Student Attitudes and Faculty Reflection

ERIC Educational Resources Information Center

Bishop, Catharine F.; Caston, Michael I.; King, Cheryl A.

2014-01-01

Learner-centered environments effectively implement multiple teaching techniques to enhance students' higher education experience and provide them with greater control over their academic learning. This qualitative study involves an exploration of the eight reasons for learner-centered teaching found in Terry Doyle's 2008 book, "Helping…

Using Questioning to Stimulate Mathematical Thinking

ERIC Educational Resources Information Center

Way, Jenni

2008-01-01

Good questioning techniques have long been regarded as a fundamental tool of effective teachers and research has found that "differences in students' thinking and reasoning could be attributed to the type of questions that teachers asked" (Wood, 2002). Past research shows that 93% of teacher questions were "lower order" knowledge-based questions…

Using the Film JFK To Teach Critical Thinking.

ERIC Educational Resources Information Center

Bassham, Gregory; Nardone, Henry

1997-01-01

A college instructional module uses the film "JFK" and related reading materials to convince even the less motivated students that reasoning abilities can be of significant personal and public value. Small groups are assigned presentations based on research and readings. Student response has been enthusiastic and the technique has been…

Interaction Pattern Analysis in cMOOCs Based on the Connectivist Interaction and Engagement Framework

ERIC Educational Resources Information Center

Wang, Zhijun; Anderson, Terry; Chen, Li; Barbera, Elena

2017-01-01

Connectivist learning is interaction-centered learning. A framework describing interaction and cognitive engagement in connectivist learning was constructed using logical reasoning techniques. The framework and analysis was designed to help researchers and learning designers understand and adapt the characteristics and principles of interaction in…

Thinking Like Researchers: An ESL Project that Investigates Local Communities

ERIC Educational Resources Information Center

McPherron, Paul; Randolph, Patrick T.

2013-01-01

Drawing on task-based and intercultural teaching approaches, this article presents an ESL classroom project at two different university settings in which students investigate aspects of their local communities through the use of ethnographic and observational research techniques. For related reasons, the instructors at each university developed…

A Comparison of Two Approaches to Beta-Flexible Clustering.

ERIC Educational Resources Information Center

Belbin, Lee; And Others

1992-01-01

A method for hierarchical agglomerative polythetic (multivariate) clustering, based on unweighted pair group using arithmetic averages (UPGMA) is compared with the original beta-flexible technique, a weighted average method. Reasons the flexible UPGMA strategy is recommended are discussed, focusing on the ability to recover cluster structure over…

Intelligent Tutors in Immersive Virtual Environments

ERIC Educational Resources Information Center

Yan, Peng; Slator, Brian M.; Vender, Bradley; Jin, Wei; Kariluoma, Matti; Borchert, Otto; Hokanson, Guy; Aggarwal, Vaibhav; Cosmano, Bob; Cox, Kathleen T.; Pilch, André; Marry, Andrew

2013-01-01

Research into virtual role-based learning has progressed over the past decade. Modern issues include gauging the difficulty of designing a goal system capable of meeting the requirements of students with different knowledge levels, and the reasonability and possibility of taking advantage of the well-designed formula and techniques served in other…

A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis.

PubMed

Gu, Dongxiao; Liang, Changyong; Zhao, Huimin

2017-03-01

We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer decision support system, oncologists can obtain powerful information or knowledge, complementing their own experiential knowledge, in their medical decision making. We observed two problems in applying standard CBR to this context: the abundance of different types of attributes and the difficulty in eliciting appropriate attribute weights from human experts. We therefore used a distance measure named weighted heterogeneous value distance metric, which can better deal with both continuous and discrete attributes simultaneously than the standard Euclidean distance, and a genetic algorithm for learning the attribute weights involved in this distance measure automatically. We evaluated our CBR system in two case studies, related to benign/malignant tumor prediction and secondary cancer prediction, respectively. Weighted heterogeneous value distance metric with genetic algorithm for weight learning outperformed several alternative attribute matching methods and several classification methods by at least 3.4%, reaching 0.938, 0.883, 0.933, and 0.984 in the first case study, and 0.927, 0.842, 0.939, and 0.989 in the second case study, in terms of accuracy, sensitivity×specificity, F measure, and area under the receiver operating characteristic curve, respectively. The evaluation result indicates the potential of CBR in the breast cancer diagnosis domain. Copyright © 2017 Elsevier B.V. All rights reserved.

Process-Based Governance in Public Administrations Using Activity-Based Costing

NASA Astrophysics Data System (ADS)

Becker, Jörg; Bergener, Philipp; Räckers, Michael

Decision- and policy-makers in public administrations currently lack on missing relevant information for sufficient governance. In Germany the introduction of New Public Management and double-entry accounting enable public administrations to get the opportunity to use cost-centered accounting mechanisms to establish new governance mechanisms. Process modelling in this case can be a useful instrument to help the public administrations decision- and policy-makers to structure their activities and capture relevant information. In combination with approaches like Activity-Based Costing, higher management level can be supported with a reasonable data base for fruitful and reasonable governance approaches. Therefore, the aim of this article is combining the public sector domain specific process modelling method PICTURE and concept of activity-based costing for supporting Public Administrations in process-based Governance.

Supervised classification of aerial imagery and multi-source data fusion for flood assessment

NASA Astrophysics Data System (ADS)

Sava, E.; Harding, L.; Cervone, G.

2015-12-01

Floods are among the most devastating natural hazards and the ability to produce an accurate and timely flood assessment before, during, and after an event is critical for their mitigation and response. Remote sensing technologies have become the de-facto approach for observing the Earth and its environment. However, satellite remote sensing data are not always available. For these reasons, it is crucial to develop new techniques in order to produce flood assessments during and after an event. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. This research presents a fusion technique using satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and tweets. A new computational methodology is proposed based on machine learning algorithms to automatically identify water pixels in CAP imagery. Specifically, wavelet transformations are paired with multiple classifiers, run in parallel, to build models discriminating water and non-water regions. The learned classification models are first tested against a set of control cases, and then used to automatically classify each image separately. A measure of uncertainty is computed for each pixel in an image proportional to the number of models classifying the pixel as water. Geo-tagged tweets are continuously harvested and stored on a MongoDB and queried in real time. They are fused with CAP classified data, and with satellite remote sensing derived flood extent results to produce comprehensive flood assessment maps. The final maps are then compared with FEMA generated flood extents to assess their accuracy. The proposed methodology is applied on two test cases, relative to the 2013 floods in Boulder CO, and the 2015 floods in Texas.

Is it just religious practice? Exploring patients' reasons for choosing a faith-based primary health clinic over their local public sector primary health clinic.

PubMed

Porter, James D; Bresick, Graham

2017-06-29

Person-centred, re-engineered primary health care (PHC) is a national and global priority. Faith-based health care is a significant provider of PHC in sub-Saharan Africa, but there is limited published data on the reasons for patient choice of faith-based health care, particularly in South Africa. The primary objective was to determine and explore the reasons for patient choice of a faith-based primary care clinic over their local public sector primary care clinic, and secondarily to determine to what extent these reasons were influenced by demography. The study was conducted at Jubilee Health Centre (JHC), a faith-based primary care clinic attached to Jubilee Community Church in Cape Town, South Africa. Focus groups, using the nominal group technique, were conducted with JHC patients and used to generate ranked reasons for attending the clinic. These were collated into the top 15 reasons and incorporated into a quantitative questionnaire which was administered to adult patients attending JHC. A total of 164 patients were surveyed (a response rate of 92.4%) of which 68.3% were female and 57.9% from the Democratic Republic of the Congo (DRC). Of patients surveyed, 98.2% chose to attend JHC because 'the staff treat me with respect', 96.3% because 'the staff are friendly' and 96.3% because 'the staff take time to listen to me'. The reason 'it is a Christian clinic' was chosen by 70.1% of patients. 'The staff speak my home language' was given as a reason by 61.1% of DRC patients and 37.1% of South African patients. 'The clinic is close to me' was chosen by 66.6% of Muslims and 40.8% of Christians. Patients chose to attend JHC (a faith-based primary care clinic) because of the quality of care received. They emphasised the staff-patient relationship and patient-centredness rather than the clinic's religious practices (prayer with patients). These findings may be important in informing efforts to improve public sector primary care.

Trends in Orbital Decompression Techniques of Surveyed American Society of Ophthalmic Plastic and Reconstructive Surgery Members.

PubMed

Reich, Shani S; Null, Robert C; Timoney, Peter J; Sokol, Jason A

To assess current members of the American Society of Ophthalmic Plastic and Reconstructive Surgery (ASOPRS) regarding preference in surgical techniques for orbital decompression in Graves' disease. A 10-question web-based, anonymous survey was distributed to oculoplastic surgeons utilizing the ASOPRS listserv. The questions addressed the number of years of experience performing orbital decompression surgery, preferred surgical techniques, and whether orbital decompression was performed in collaboration with an ENT surgeon. Ninety ASOPRS members participated in the study. Most that completed the survey have performed orbital decompression surgery for >15 years. The majority of responders preferred a combined approach of floor and medial wall decompression or balanced lateral and medial wall decompression; only a minority selected a technique limited to 1 wall. Those surgeons who perform fat decompression were more likely to operate in collaboration with ENT. Most surgeons rarely remove the orbital strut, citing risk of worsening diplopia or orbital dystopia except in cases of optic nerve compression or severe proptosis. The most common reason given for performing orbital decompression was exposure keratopathy. The majority of surgeons perform the surgery without ENT involvement, and number of years of experience did not correlate significantly with collaboration with ENT. The majority of surveyed ASOPRS surgeons prefer a combined wall approach over single wall approach to initial orbital decompression. Despite the technological advances made in the field of modern endoscopic surgery, no single approach has been adopted by the ASOPRS community as the gold standard.

Candida endophthalmitis after heroin abuse.

PubMed

Malecaze, F; Arne, J L; Bec, P; Séguéla, J P; Linas, M D; Recco, P; Béssières, M H

1985-11-01

Three cases of ocular candidosis involving heroin abusers have been observed in 1983 in Toulouse department of ophthalmology. These three patients had used iranian brown heroin. Twenty similar cases have been published in these last years. This new pathology can be explained on two reasons. The first is that the drug abusers have some immunity pertubation; however, immunity exploration in these patients does not reveal any immunodeficiency. The second reason, certainly more important, is the method of using heroin. The diagnosis of Candida endophthalmitis of course based on clinical context must be proved by biological tests. Candida albicans is never identified in aqueous humor. For this reason, it seems very interesting to detect anti-candida antibodies in aqueous humor. It has been used as methods of dosage laser Nephelemetry for IgG and immunofluorescence for candidosis antibodies. The criterion used is similar to the toxoplasmosis coefficient established by Desmonts (3). In two cases, this test was the only way that permits us to have certitude of candidosis ocular diagnosis. Otherwise the observations show that anterior chamber punction is more significant when there is an anterior uveitis.

Argumentation and Equity in Inquiry-Based Science Instruction: Reasoning Patterns of Teachers and Students

NASA Astrophysics Data System (ADS)

Irish, Tobias E. L.

This multiple case study explores issues of equity in science education through an examination of how teachers' reasoning patterns compare with students' reasoning patterns during inquiry-based lessons. It also examines the ways in which teachers utilize students' cultural and linguistic resources, or funds of knowledge, during inquiry-based lessons and the ways in which students utilize their funds of knowledge, during inquiry-based lessons. Three middle school teachers and a total of 57 middle school students participated in this study. The data collection involved classroom observations and multiple interviews with each of the teachers individually and with small groups of students. The findings indicate that the students are capable of far more complex reasoning than what was elicited by the lessons observed or what was modeled and expected by the teachers, but that during the inquiry-based lessons they conformed to the more simplistic reasoning patterns they perceived as the expected norm of classroom dialogue. The findings also indicate that the students possess funds of knowledge that are relevant to science topics, but very seldom use these funds in the context of their inquiry-based lessons. In addition, the teachers in this study very seldom worked to elicit students' use of their funds in these contexts. The few attempts they did make involved the use of analogies, examples, or questions. The findings from this study have implications for both teachers and teacher educators in that they highlight similarities and differences in reasoning that can help teachers establish instructional congruence and facilitate more equitable science instruction. They also provide insight into how students' cultural and linguistic resources are utilized during inquiry-based science lessons.

Problem Representation, Background Evidence, Analysis, Recommendation: An Oral Case Presentation Tool to Promote Diagnostic Reasoning.

PubMed

Carter, Cristina; Akar-Ghibril, Nicole; Sestokas, Jeff; Dixon, Gabrina; Bradford, Wilhelmina; Ottolini, Mary

2018-03-01

Oral case presentations provide an opportunity for trainees to communicate diagnostic reasoning at the bedside. However, few tools exist to enable faculty to provide effective feedback. We developed a tool to assess diagnostic reasoning and communication during oral case presentations. Published by Elsevier Inc.

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

A Semi-Supervised Learning Approach to Enhance Health Care Community–Based Question Answering: A Case Study in Alcoholism

PubMed Central

Klabjan, Diego; Jonnalagadda, Siddhartha Reddy

2016-01-01

Background Community-based question answering (CQA) sites play an important role in addressing health information needs. However, a significant number of posted questions remain unanswered. Automatically answering the posted questions can provide a useful source of information for Web-based health communities. Objective In this study, we developed an algorithm to automatically answer health-related questions based on past questions and answers (QA). We also aimed to understand information embedded within Web-based health content that are good features in identifying valid answers. Methods Our proposed algorithm uses information retrieval techniques to identify candidate answers from resolved QA. To rank these candidates, we implemented a semi-supervised leaning algorithm that extracts the best answer to a question. We assessed this approach on a curated corpus from Yahoo! Answers and compared against a rule-based string similarity baseline. Results On our dataset, the semi-supervised learning algorithm has an accuracy of 86.2%. Unified medical language system–based (health related) features used in the model enhance the algorithm’s performance by proximately 8%. A reasonably high rate of accuracy is obtained given that the data are considerably noisy. Important features distinguishing a valid answer from an invalid answer include text length, number of stop words contained in a test question, a distance between the test question and other questions in the corpus, and a number of overlapping health-related terms between questions. Conclusions Overall, our automated QA system based on historical QA pairs is shown to be effective according to the dataset in this case study. It is developed for general use in the health care domain, which can also be applied to other CQA sites. PMID:27485666

Monitoring real-time navigation processes using the automated reasoning tool (ART)

NASA Technical Reports Server (NTRS)

Maletz, M. C.; Culbert, C. J.

1985-01-01

An expert system is described for monitoring and controlling navigation processes in real-time. The ART-based system features data-driven computation, accommodation of synchronous and asynchronous data, temporal modeling for individual time intervals and chains of time intervals, and hypothetical reasoning capabilities that consider alternative interpretations of the state of navigation processes. The concept is illustrated in terms of the NAVEX system for monitoring and controlling the high speed ground navigation console for Mission Control at Johnson Space Center. The reasoning processes are outlined, including techniques used to consider alternative data interpretations. Installation of the system has permitted using a single operator, instead of three, to monitor the ascent and entry phases of a Shuttle mission.

Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.

PubMed

Salim, Agus; Mackinnon, Andrew; Christensen, Helen; Griffiths, Kathleen

2008-09-30

The pre-test-post-test design (PPD) is predominant in trials of psychotherapeutic treatments. Missing data due to withdrawals present an even bigger challenge in assessing treatment effectiveness under the PPD than under designs with more observations since dropout implies an absence of information about response to treatment. When confronted with missing data, often it is reasonable to assume that the mechanism underlying missingness is related to observed but not to unobserved outcomes (missing at random, MAR). Previous simulation and theoretical studies have shown that, under MAR, modern techniques such as maximum-likelihood (ML) based methods and multiple imputation (MI) can be used to produce unbiased estimates of treatment effects. In practice, however, ad hoc methods such as last observation carried forward (LOCF) imputation and complete-case (CC) analysis continue to be used. In order to better understand the behaviour of these methods in the PPD, we compare the performance of traditional approaches (LOCF, CC) and theoretically sound techniques (MI, ML), under various MAR mechanisms. We show that the LOCF method is seriously biased and conclude that its use should be abandoned. Complete-case analysis produces unbiased estimates only when the dropout mechanism does not depend on pre-test values even when dropout is related to fixed covariates including treatment group (covariate-dependent: CD). However, CC analysis is generally biased under MAR. The magnitude of the bias is largest when the correlation of post- and pre-test is relatively low.

Evaluation of CFD Turbulent Heating Prediction Techniques and Comparison With Hypersonic Experimental Data

NASA Technical Reports Server (NTRS)

Dilley, Arthur D.; McClinton, Charles R. (Technical Monitor)

2001-01-01

Results from a study to assess the accuracy of turbulent heating and skin friction prediction techniques for hypersonic applications are presented. The study uses the original and a modified Baldwin-Lomax turbulence model with a space marching code. Grid converged turbulent predictions using the wall damping formulation (original model) and local damping formulation (modified model) are compared with experimental data for several flat plates. The wall damping and local damping results are similar for hot wall conditions, but differ significantly for cold walls, i.e., T(sub w) / T(sub t) < 0.3, with the wall damping heating and skin friction 10-30% above the local damping results. Furthermore, the local damping predictions have reasonable or good agreement with the experimental heating data for all cases. The impact of the two formulations on the van Driest damping function and the turbulent eddy viscosity distribution for a cold wall case indicate the importance of including temperature gradient effects. Grid requirements for accurate turbulent heating predictions are also studied. These results indicate that a cell Reynolds number of 1 is required for grid converged heating predictions, but coarser grids with a y(sup +) less than 2 are adequate for design of hypersonic vehicles. Based on the results of this study, it is recommended that the local damping formulation be used with the Baldwin-Lomax and Cebeci-Smith turbulence models in design and analysis of Hyper-X and future hypersonic vehicles.

Optimal Compressed Sensing and Reconstruction of Unstructured Mesh Datasets

DOE PAGES

Salloum, Maher; Fabian, Nathan D.; Hensinger, David M.; ...

2017-08-09

Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate itsmore » usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Finally, our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.« less

Validation techniques of agent based modelling for geospatial simulations

NASA Astrophysics Data System (ADS)

Darvishi, M.; Ahmadi, G.

2014-10-01

One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

The management of lower gastrointestinal bleeding.

PubMed

Marion, Y; Lebreton, G; Le Pennec, V; Hourna, E; Viennot, S; Alves, A

2014-06-01

Lower gastrointestinal (LGI) bleeding is generally less severe than upper gastrointestinal (UGI) bleeding with spontaneous cessation of bleeding in 80% of cases and a mortality of 2-4%. However, unlike UGI bleeding, there is no consensual agreement about management. Once the patient has been stabilized, the main objective and greatest difficulty is to identify the location of bleeding in order to provide specific appropriate treatment. While upper endoscopy and colonoscopy remain the essential first-line examinations, the development and availability of angiography have made this an important imaging modality for cases of active bleeding; they allow diagnostic localization of bleeding and guide subsequent therapy, whether therapeutic embolization, interventional colonoscopy or, if other techniques fail or are unavailable, surgery directed at the precise site of bleeding. Furthermore, newly developed endoscopic techniques, particularly video capsule enteroscopy, now allow minimally invasive exploration of the small intestine; if this is positive, it will guide subsequent assisted enteroscopy or surgery. Other small bowel imaging techniques include enteroclysis by CT or magnetic resonance imaging. At the present time, exploratory surgery is no longer a first-line approach. In view of the lesser gravity of LGI bleeding, it is most reasonable to simply stabilize the patient initially for subsequent transfer to a specialized center, if minimally invasive techniques are not available at the local hospital. In all cases, the complexity and diversity of LGI bleeding require a multidisciplinary collaboration involving the gastroenterologist, radiologist, intensivist and surgeon to optimize diagnosis and treatment of the patient. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Clinical Reasoning Tasks and Resident Physicians: What Do They Reason About?

PubMed

McBee, Elexis; Ratcliffe, Temple; Goldszmidt, Mark; Schuwirth, Lambert; Picho, Katherine; Artino, Anthony R; Masel, Jennifer; Durning, Steven J

2016-07-01

A framework of clinical reasoning tasks thought to occur in a clinical encounter was recently developed. It proposes that diagnostic and therapeutic reasoning comprise 24 tasks. The authors of this current study used this framework to investigate what internal medicine residents reason about when they approach straightforward clinical cases. Participants viewed three video-recorded clinical encounters portraying common diagnoses. After each video, participants completed a post encounter form and think-aloud protocol. Two authors analyzed transcripts from the think-aloud protocols using a constant comparative approach. They conducted iterative coding of the utterances, classifying each according to the framework of clinical reasoning tasks. They evaluated the type, number, and sequence of tasks the residents used. Ten residents participated in the study in 2013-2014. Across all three cases, the residents employed 14 clinical reasoning tasks. Nearly all coded tasks were associated with framing the encounter or diagnosis. The order in which residents used specific tasks varied. The average number of tasks used per case was as follows: Case 1, 4.4 (range 1-10); Case 2, 4.6 (range 1-6); and Case 3, 4.7 (range 1-7). The residents used some tasks repeatedly; the average number of task utterances was 11.6, 13.2, and 14.7 for, respectively, Case 1, 2, and 3. Results suggest that the use of clinical reasoning tasks occurs in a varied, not sequential, process. The authors provide suggestions for strengthening the framework to more fully encompass the spectrum of reasoning tasks that occur in residents' clinical encounters.

Seismic Hazard Analysis as a Controlling Technique of Induced Seismicity in Geothermal Systems

NASA Astrophysics Data System (ADS)

Convertito, V.; Sharma, N.; Maercklin, N.; Emolo, A.; Zollo, A.

2011-12-01

The effect of induced seismicity of geothermal systems during stimulation and fluid circulation can cover a wide range of values from light and unfelt to severe and damaging. If the design of a modern geothermal system requires the largest efficiency to be obtained from the social point of view it is required that the system could be managed in order to reduce possible impact in advance. In this framework, automatic control of the seismic response of the stimulated reservoir is nowadays mandatory, particularly in proximity of densely populated areas. Recently, techniques have been proposed for this purpose mainly based on the concept of the traffic light. This system provides a tool to decide the level of stimulation rate based on the real-time analysis of the induced seismicity and the ongoing ground motion values. However, in some cases the induced effect can be delayed with respect to the time when the reservoir is stimulated. Thus, a controlling system technique able to estimate the ground motion levels for different time scales can help to better control the geothermal system. Here we present an adaptation of the classical probabilistic seismic hazard analysis to the case where the seismicity rate as well as the propagation medium properties are not constant with time. We use a non-homogeneous seismicity model for modeling purposes, in which the seismicity rate and b-value of the recurrence relationship change with time. Additionally, as a further controlling procedure, we propose a moving time window analysis of the recorded peak ground-motion values aimed at monitoring the changes in the propagation medium. In fact, for the same set of magnitude values recorded at the same stations, we expect that on average peak ground motion values attenuate in same way. As a consequence, the residual differences can be reasonably ascribed to changes in medium properties. These changes can be modeled and directly introduced in the hazard integral. We applied the proposed technique to a training dataset of induced earthquakes recorded by Berkeley-Geysers network, which is installed in The Geysers geothermal area in Northern California. The reliability of the techniques is then tested by using a different dataset performing seismic hazard analysis in a time-evolving approach, which provides with ground-motion values having fixed probabilities of exceedence. Those values can be finally compared with the observations by using appropriate statistical tests.

Receptive field optimisation and supervision of a fuzzy spiking neural network.

PubMed

Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather

2011-04-01

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

NASA Astrophysics Data System (ADS)

Sumarno; Ibrahim, M.; Supardi, Z. A. I.

2018-03-01

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

Corticotomy facilitated orthodontics: Review of a technique

PubMed Central

AlGhamdi, Ali Saad Thafeed

2009-01-01

Corticotomy found to be effective in accelerating orthodontic treatment. The most important factors in the success of this technique is proper case selection and careful surgical and orthodontic treatment. Corticotomy facilitated orthodontics advocated for comprehensive fixed orthodontic appliances in conjunction with full thickness flaps and labial and lingual corticotomies around teeth to be moved. Bone graft should be applied directly over the bone cuts and the flap sutured in place. Tooth movement should be initiated two weeks after the surgery, and every two weeks thereafter by activation of the orthodontic appliance. Orthodontic treatment time with this technique will be reduced to one-third the time of conventional orthodontics. Alveolar augmentation of labial and lingual cortical plates were used in an effort to enhance and strengthen the periodontium, reasoning that the addition of bone to alveolar housing of the teeth, using modern bone grafting techniques, ensures root coverage as the dental arch expanded. Corticotomy facilitated orthodontics is promising procedure but only few cases were reported in the literature. Controlled clinical and histological studies are needed to understand the biology of tooth movement with this procedure, the effect on teeth and bone, post-retention stability, measuring the volume of mature bone formation, and determining the status of the periodontium and roots after treatment. PMID:23960473

Generic project definitions for improvement of health care delivery: a case-based approach.

PubMed

Niemeijer, Gerard C; Does, Ronald J M M; de Mast, Jeroen; Trip, Albert; van den Heuvel, Jaap

2011-01-01

The purpose of this article is to create actionable knowledge, making the definition of process improvement projects in health care delivery more effective. This study is a retrospective analysis of process improvement projects in hospitals, facilitating a case-based reasoning approach to project definition. Data sources were project documentation and hospital-performance statistics of 271 Lean Six Sigma health care projects from 2002 to 2009 of general, teaching, and academic hospitals in the Netherlands and Belgium. Objectives and operational definitions of improvement projects in the sample, analyzed and structured in a uniform format and terminology. Extraction of reusable elements of earlier project definitions, presented in the form of 9 templates called generic project definitions. These templates function as exemplars for future process improvement projects, making the selection, definition, and operationalization of similar projects more efficient. Each template includes an explicated rationale, an operationalization in the form of metrics, and a prototypical example. Thus, a process of incremental and sustained learning based on case-based reasoning is facilitated. The quality of project definitions is a crucial success factor in pursuits to improve health care delivery. We offer 9 tried and tested improvement themes related to patient safety, patient satisfaction, and business-economic performance of hospitals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miyasaka, Y; Kadoya, N; Ito, K

Purpose: Accurate deformable image registration (DIR) between external beam radiotherapy (EBRT) and HDR brachytherapy (BT) CT images in cervical cancer is challenging. DSC has been evaluated only on the basis of the consistency of the structure, and its use does not guarantee an anatomically reasonable deformation. We evaluate the DIR accuracy for cervical cancer with DSC and anatomical landmarks using a 3D-printed pelvis phantom. Methods: A 3D-printed, deformable female pelvis phantom was created on the basis of the patient’s CT image. Urethane and silicon were used as materials for creating the uterus and bladder, respectively, in the phantom. We performedmore » DIR in two cases: case-A with a full bladder (170 ml) in both the EBRT and BT images and case-B with a full bladder in the BT image and a half bladder (100 ml) in the EBRT image. DIR was evaluated using DSCs and 70 uterus and bladder landmarks. A Hybrid intensity and structure DIR algorithm with two settings (RayStation) was used. Results: In the case-A, DSCs of the intensity-based DIR were 0.93 and 0.85 for the bladder and uterus, respectively, whereas those of hybrid-DIR were 0.98 and 0.96, respectively. The mean landmark error values of intensity-based DIR were 0.73±0.29 and 1.70±0.19 cm for the bladder and uterus, respectively, whereas those of Hybrid-DIR were 0.43±0.33 and 1.23±0.25 cm, respectively. In both cases, the Hybrid-DIR accuracy was better than the intensity-based DIR accuracy for both evaluation methods. However, for several bladder landmarks, the Hybrid-DIR landmark errors were larger than the corresponding intensity-based DIR errors (e.g., 2.26 vs 1.25 cm). Conclusion: Our results demonstrate that Hybrid-DIR can perform with a better accuracy than the intensity-based DIR for both DSC and landmark errors; however, Hybrid-DIR shows a larger landmark error for some landmarks because the technique focuses on both the structure and intensity.« less

[The reasons why 13 MK1 attachment were re-fabricated and some methods for improvement].

PubMed

Wu, Zhi-hong; Zhang, Xue-jun; Zhao, Jun

2013-12-01

To investigate the reasons why 13 MK1 attachment were re-fabricated and to suggest some improvement methods. Mechanics and denture production technology were reviewed in 13 cases with MK1 attachment denture to determine the causes of failure. In some cases, MK1 attachments were poorly designed, while in other cases problems were found during denture design and production process due to limited experiences at the initial stage. MK1 attachments were re-done based on the specific cause and the outcome was good after 1-1.5 years of follow-up. When using MK1 attachment, prosthodontists should be familiar with the characteristics and indications of MK1 attachment. Meanwhile, we should strengthen doctor-patient communication and follow up patients timely to improve the success rate of MK1 attached denture repair.

Interface between psychiatry and the law on the issue of murder.

PubMed

Bell, C C

1980-11-01

Not guilty by reason of insanity is a legal defense of murder. The acquittal of such an act is based on the court finding that the crime was due to the defendant's mental illness and not to criminal intent. The author presents characteristic case histories, as seen by him in the role of expert witness, that may serve as paradigms when the doctrine "not guilty by reason of insanity" is an appropriate defense.

Interface Between Psychiatry and the Law on the Issue of Murder

PubMed Central

Bell, Carl C.

1980-01-01

Not guilty by reason of insanity is a legal defense of murder. The acquittal of such an act is based on the court finding that the crime was due to the defendant's mental illness and not to criminal intent. The author presents characteristic case histories, as seen by him in the role of expert witness, that may serve as paradigms when the doctrine “not guilty by reason of insanity” is an appropriate defense. PMID:7441789

Interpolation/extrapolation technique with application to hypervelocity impact of space debris

NASA Technical Reports Server (NTRS)

Rule, William K.

1992-01-01

A new technique for the interpolation/extrapolation of engineering data is described. The technique easily allows for the incorporation of additional independent variables, and the most suitable data in the data base is automatically used for each prediction. The technique provides diagnostics for assessing the reliability of the prediction. Two sets of predictions made for known 5-degree-of-freedom, 15-parameter functions using the new technique produced an average coefficient of determination of 0.949. Here, the technique is applied to the prediction of damage to the Space Station from hypervelocity impact of space debris. A new set of impact data is presented for this purpose. Reasonable predictions for bumper damage were obtained, but predictions of pressure wall and multilayer insulation damage were poor.

Cement-in-cement stem revision for Vancouver type B periprosthetic femoral fractures after total hip arthroplasty. A 3-year follow-up of 23 cases.

PubMed

Briant-Evans, Toby W; Veeramootoo, Darmaraja; Tsiridis, Eleftherios; Hubble, Matthew J

2009-10-01

Revision surgery for periprosthetic femoral fractures around an unstable cemented femoral stem traditionally requires removal of existing cement. We propose a new technique whereby a well-fixed cement mantle can be retained in cases with simple fractures that can be reduced anatomically when a cemented revision is planned. This technique is well established in femoral stem revision, but not in association with a fracture. We treated 23 Vancouver type B periprosthetic femoral fractures by reducing the fracture and cementing a revision stem into the pre-existing cement mantle, with or without supplementary fixation. 3 patients died in the first 6 months for reasons unrelated to surgery. In addition, 1 was too frail to attend follow-up and was therefore excluded from the study, and 1 patient underwent revision surgery for a nonunion. The remaining 18 cases all healed with radiographic union after an average time of 4.4 (2-11) months. There was no sign of loosening or subsidence of the revision stems within the old cement mantle in any of these cases at the most recent follow-up after an average of 3 (0.3-9) years. Our results support the use of the cement-in-cement revision in anatomically reducible periprosthetic fractures with a well-preserved pre-existing cement mantle. This technique is particularly useful for the elderly patient and for those who are not fit for prolonged surgical procedures.

Students’ Algebraic Reasonsing In Solving Mathematical Problems With Adversity Quotient

NASA Astrophysics Data System (ADS)

Aryani, F.; Amin, S. M.; Sulaiman, R.

2018-01-01

Algebraic reasoning is a process in which students generalize mathematical ideas from a set of particular instances and express them in increasingly formal and age-appropriate ways. Using problem solving approach to develop algebraic reasoning of mathematics may enhace the long-term learning trajectory of the majority students. The purpose of this research was to describe the algebraic reasoning of quitter, camper, and climber junior high school students in solving mathematical problems. This research used qualitative descriptive method. Subjects were determined by purposive sampling. The technique of collecting data was done by task-based interviews.The results showed that the algebraic reasoning of three students in the process of pattern seeking by identifying the things that are known and asked in a similar way. But three students found the elements of pattern recognition in different ways or method. So, they are generalize the problem of pattern formation with different ways. The study of algebraic reasoning and problem solving can be a learning paradigm in the improve students’ knowledge and skills in algebra work. The goal is to help students’ improve academic competence, develop algebraic reasoning in problem solving.

Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Wang, Guang-Min; Wang, Tao; Ren, Hua-Ling; Zhang, Lin

2018-05-01

This paper studies how to generate the reasonable information of travelers’ decision in real network. This problem is very complex because the travelers’ decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers’ decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance. Supported by National Natural Science Foundation of China under Grant Nos. 71471104, 71771019, 71571109, and 71471167; The University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; The Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236; The Major Social and Livelihood Special Project of Jinan under Grant No. 20150905

The changing face of malignant hyperthermia: less fulminant, more insidious..

PubMed

Heytens, L; Forget, P; Scholtès, J L; Veyckemans, F

2015-07-01

Modern anaesthetic techniques have resulted in the clinical presentation of malignant hyperthermia to be more often indolent and/or insidious than truly fulminant, as previously known in the anaesthetic community. We present four recently referred cases to illustrate this point: one late-onset case, two patients with slowly progressive hypercapnia as the sole sign and a fourth patient with postoperative myalgias and elevated creatine kinase. We also discuss the reasons for the shift in typical clinical presentation. The more insidious character of malignant hyperthermia is most likely due to the lower triggering potency of modern volatile anaesthetics, the mitigating effects of several intravenous drugs (neuromuscular blocking agents, alpha 2 adrenergic receptor agonists, beta adrenergic blockade) or techniques (neuraxial anaesthesia) and the routine use of end-tidal CO2 monitoring leading to the early withdrawal of triggering drugs. Awareness among anaesthetists of this change in presentation is important since the clinical diagnosis is often more doubtful and, if corroborative evidence is not sought, the diagnosis may be delayed or missed altogether.

Heavy ion induced DNA-DSB in yeast and mammalian cells

NASA Technical Reports Server (NTRS)

Loebrich, M.; Ikpeme, S.; Kiefer, J.

1994-01-01

Molecular changes at the DNA are assumed to be the main cause for radiation effects in a number of organisms. During the course of the last decades techniques have been developed for measuring DNA double-strand breaks (dsb), generally assumed to be the most critical DNA lesions. The outcome of all those different approaches portrays a collection of data useful for a theoretical description of radiation action mechanisms. However, in the case of heavy ion induced DNA dsb the picture is not quite clear yet and further projects and strategies have to be developed. The biological systems studied in our group are yeast and mammalian cells. While in the case of yeast cells technical and methodical reasons highlight these organisms mammalian cells reach greater importance when dsb repair studies are performed. In both types of organisms the technique of pulsed-field gel electrophoresis (PFGE) is applied, although with different modifications and evaluation procedures mainly due to the different genome sizes.

Blind deconvolution of 2-D and 3-D fluorescent micrographs

NASA Astrophysics Data System (ADS)

Krishnamurthi, Vijaykumar; Liu, Yi-Hwa; Holmes, Timothy J.; Roysam, Badrinath; Turner, James N.

1992-06-01

This paper presents recent results of our reconstructions of 3-D data from Drosophila chromosomes as well as our simulations with a refined version of the algorithm used in the former. It is well known that the calibration of the point spread function (PSF) of a fluorescence microscope is a tedious process and involves esoteric techniques in most cases. This problem is further compounded in the case of confocal microscopy where the measured intensities are usually low. A number of techniques have been developed to solve this problem, all of which are methods in blind deconvolution. These are so called because the measured PSF is not required in the deconvolution of degraded images from any optical system. Our own efforts in this area involved the maximum likelihood (ML) method, the numerical solution to which is obtained by the expectation maximization (EM) algorithm. Based on the reasonable early results obtained during our simulations with 2-D phantoms, we carried out experiments with real 3-D data. We found that the blind deconvolution method using the ML approach gave reasonable reconstructions. Next we tried to perform the reconstructions using some 2-D data, but we found that the results were not encouraging. We surmised that the poor reconstructions were primarily due to the large values of dark current in the input data. This, coupled with the fact that we are likely to have similar data with considerable dark current from a confocal microscope prompted us to look into ways of constraining the solution of the PSF. We observed that in the 2-D case, the reconstructed PSF has a tendency to retain values larger than those of the theoretical PSF in regions away from the center (outside of those we considered to be its region of support). This observation motivated us to apply an upper bound constraint on the PSF in these regions. Furthermore, we constrain the solution of the PSF to be a bandlimited function, as in the case in the true situation. We have derived two separate approaches for implementing the constraint. One approach involves the mathematical rigors of Lagrange multipliers. This approach is discussed in another paper. The second approach involves an adaptation of the Gershberg Saxton algorithm, which ensures bandlimitedness and non-negativity of the PSF. Although the latter approach is mathematically less rigorous than the former, we currently favor it because it has a simpler implementation on a computer and has smaller memory requirements. The next section describes briefly the theory and derivation of these constraint equations using Lagrange multipliers.

You Want Me To Do What? The Cultural and Psychological Struggle of Putting a Course Online.

ERIC Educational Resources Information Center

Anderson, Sharon K.; Middleton, Val

2002-01-01

Presents a case study of the development of a Web-based online course. Discusses the culture of online instruction; conflicts in course development; presenting students with reasons for Web-based instruction; student orientation for online programs; motivation; and the need for some human interaction. (LRW)

Teleworking and Gender.

ERIC Educational Resources Information Center

Huws, Ursula; And Others

This report details a survey of 188 teleworkers throughout Europe that was supplemented by face-to-face interviews with 9 teleworkers in the United Kingdom, Sweden, and the Netherlands. The group of male and female home-based translators was chosen for two reasons: most surveys and case studies of teleworking have been company based and unable to…

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

PubMed

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

PubMed

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Learning to Explain Astronomy across Moving Frames of Reference: Exploring the Role of Classroom and Planetarium-Based Instructional Contexts

ERIC Educational Resources Information Center

Plummer, Julia Diane; Kocareli, Alicia; Slagle, Cynthia

2014-01-01

Learning astronomy involves significant spatial reasoning, such as learning to describe Earth-based phenomena and understanding space-based explanations for those phenomena as well as using the relevant size and scale information to interpret these frames of reference. This study examines daily celestial motion (DCM) as one case of how children…